meanjs/mean

Vulnerabilities

96 via 372 paths

Dependencies

1260

Source

GitHub

Commit

ed8d04c4

Find, fix and prevent vulnerabilities in your code.

Issue type
  • 96
  • 1
Severity
  • 2
  • 46
  • 43
  • 6
Status
  • 97
  • 0
  • 0

critical severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.3.0.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. It is possible to add or modify properties to the Object prototype through a malicious template. This may allow attackers to crash the application or execute Arbitrary Code in specific conditions.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 3.0.8, 4.5.3 or higher.

References

critical severity

Improper Input Validation

  • Vulnerable module: xmldom
  • Introduced through: passport-twitter@1.0.4

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.

Affected versions of this package are vulnerable to Improper Input Validation due to parsing XML that is not well-formed, and contains multiple top-level elements. All the root nodes are being added to the childNodes collection of the Document, without reporting or throwing any error.

Workarounds

One of the following approaches might help, depending on your use case:

  1. Instead of searching for elements in the whole DOM, only search in the documentElement.

  2. Reject a document with a document that has more than 1 childNode.

PoC

var DOMParser = require('xmldom').DOMParser;
var xmlData = '<?xml version="1.0" encoding="UTF-8"?>\n' +
'<root>\n' +
'  <branch girth="large">\n' +
'    <leaf color="green" />\n' +
'  </branch>\n' +
'</root>\n' +
'<root>\n' +
'  <branch girth="twig">\n' +
'    <leaf color="gold" />\n' +
'  </branch>\n' +
'</root>\n';
var xmlDOM = new DOMParser().parseFromString(xmlData);
console.log(xmlDOM.toString());

This will result with the following output:

<?xml version="1.0" encoding="UTF-8"?><root>
  <branch girth="large">
    <leaf color="green"/>
  </branch>
</root>
<root>
  <branch girth="twig">
    <leaf color="gold"/>
  </branch>
</root>

Remediation

There is no fixed version for xmldom.

References

high severity

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to NULL Pointer Dereference in the function Sass::Functions::selector_append which could be leveraged by an attacker to cause a denial of service (application crash) or possibly have unspecified other impact. node-sass is affected by this vulnerability due to its bundled usage of libsass.

Remediation

There is no fixed version for node-sass.

References

high severity

Use After Free

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Use After Free via the SharedPtr class in SharedPtr.cpp (or SharedPtr.hpp) that may cause a denial of service (application crash) or possibly have unspecified other impact. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

There is no fixed version for node-sass.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: cross-spawn
  • Introduced through: gulp-eslint@4.0.2, gulp-imagemin@5.0.3 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 cross-spawn@5.1.0
    Remediation: Upgrade to gulp-eslint@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 exec-buffer@3.2.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 exec-buffer@3.2.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 exec-buffer@3.2.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 bin-check@4.1.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 bin-check@4.1.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 bin-check@4.1.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 bin-check@4.1.0 execa@0.7.0 cross-spawn@5.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 cross-spawn@3.0.1
    Remediation: Upgrade to gulp-sass@5.0.0.

…and 10 more

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to improper input sanitization. An attacker can increase the CPU usage and crash the program by crafting a very large and well crafted string.

PoC

const { argument } = require('cross-spawn/lib/util/escape');
var str = "";
for (var i = 0; i < 1000000; i++) {
  str += "\\";
}
str += "◎";

console.log("start")
argument(str)
console.log("end")

// run `npm install cross-spawn` and `node attack.js` 
// then the program will stuck forever with high CPU usage

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade cross-spawn to version 6.0.6, 7.0.5 or higher.

References

high severity

Improper Neutralization of Special Elements in Data Query Logic

  • Vulnerable module: mongoose
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21
    Remediation: Upgrade to mongoose@6.13.5.

Overview

mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.

Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Data Query Logic due to the improper handling of $where in match queries. An attacker can manipulate search queries to inject malicious code.

Remediation

Upgrade mongoose to version 6.13.5, 7.8.3, 8.8.3 or higher.

References

high severity

Improper Neutralization of Special Elements in Data Query Logic

  • Vulnerable module: mongoose
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21
    Remediation: Upgrade to mongoose@6.13.6.

Overview

mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.

Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Data Query Logic due to the improper use of a $where filter in conjunction with the populate() match. An attacker can manipulate search queries to retrieve or alter information without proper authorization by injecting malicious input into the query.

Note: This vulnerability derives from an incomplete fix of CVE-2024-53900

Remediation

Upgrade mongoose to version 6.13.6, 7.8.4, 8.9.5 or higher.

References

high severity

Command Injection

  • Vulnerable module: nodemailer
  • Introduced through: nodemailer@4.0.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 nodemailer@4.0.1
    Remediation: Upgrade to nodemailer@6.4.16.

Overview

nodemailer is an Easy as cake e-mail sending from your Node.js applications

Affected versions of this package are vulnerable to Command Injection. Use of crafted recipient email addresses may result in arbitrary command flag injection in sendmail transport for sending mails.

PoC

-bi@example.com (-bi Initialize the alias database.)
-d0.1a@example.com (The option -d0.1 prints the version of sendmail and the options it was compiled with.)
-Dfilename@example.com (Debug output ffile)

Remediation

Upgrade nodemailer to version 6.4.16 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic was insufficient when extracting tar files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both \ and / characters as path separators. However, \ is a valid filename character on posix systems.

By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location. This can lead to extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite.

Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar archive contained a directory at FOO, followed by a symbolic link named foo, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but not from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the FOO directory would then be placed in the target of the symbolic link, thinking that the directory had already been created.

Remediation

Upgrade tar to version 6.1.7, 5.0.8, 4.4.16 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain two directories and a symlink with names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts. A specially crafted tar archive can include directories with two forms of the path that resolve to the same file system entity, followed by a symbolic link with a name in the first form, lastly followed by a file using the second form. This leads to bypassing node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and extracting arbitrary files into that location.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain .. path portions, and resolving the sanitized paths against the extraction target directory.

This logic is insufficient on Windows systems when extracting tar files that contain a path that is not an absolute path, but specify a drive letter different from the extraction target, such as C:some\path. If the drive letter does not match the extraction target, for example D:\extraction\dir, then the result of path.resolve(extractionDirectory, entryPath) resolves against the current working directory on the C: drive, rather than the extraction target directory.

Additionally, a .. portion of the path can occur immediately after the drive letter, such as C:../foo, and is not properly sanitized by the logic that checks for .. within the normalized and split portions of the path.

Note: This only affects users of node-tar on Windows systems.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: xmldom
  • Introduced through: passport-twitter@1.0.4

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.

Affected versions of this package are vulnerable to Prototype Pollution through the copy() function in dom.js. Exploiting this vulnerability is possible via the p variable.

DISPUTED This vulnerability has been disputed by the maintainers of the package. Currently the only viable exploit that has been demonstrated is to pollute the target object (rather then the global object which is generally the case for Prototype Pollution vulnerabilities) and it is yet unclear if this limited attack vector exposes any vulnerability in the context of this package.

See the linked GitHub Issue for full details on the discussion around the legitimacy and potential revocation of this vulnerability.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

There is no fixed version for xmldom.

References

high severity

Asymmetric Resource Consumption (Amplification)

  • Vulnerable module: body-parser
  • Introduced through: gulp-refresh@1.1.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 body-parser@1.14.2

Overview

Affected versions of this package are vulnerable to Asymmetric Resource Consumption (Amplification) via the extendedparser and urlencoded functions when the URL encoding process is enabled. An attacker can flood the server with a large number of specially crafted requests.

Remediation

Upgrade body-parser to version 1.20.3 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The function zipObjectDeep can be tricked into adding or modifying properties of the Object prototype. These properties will be present on all objects.

PoC

const _ = require('lodash');

_.zipObjectDeep(['__proto__.z'],[123]);

console.log(z); // 123

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.20 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient symlink protection. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain both a directory and a symlink with the same name as the directory. This order of operations results in the directory being created and added to the node-tar directory cache. When a directory is present in the directory cache, subsequent calls to mkdir for that directory are skipped. However, this is also where node-tar checks for symlinks occur. By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location.

Remediation

Upgrade tar to version 3.2.3, 4.4.15, 5.0.7, 6.1.2 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient absolute path sanitization.

node-tar aims to prevent extraction of absolute file paths by turning absolute paths into relative paths when the preservePaths flag is not set to true. This is achieved by stripping the absolute path root from any absolute file paths contained in a tar file. For example, the path /home/user/.bashrc would turn into home/user/.bashrc.

This logic is insufficient when file paths contain repeated path roots such as ////home/user/.bashrc. node-tar only strips a single path root from such paths. When given an absolute file path with repeating path roots, the resulting path (e.g. ///home/user/.bashrc) still resolves to an absolute path.

Remediation

Upgrade tar to version 3.2.2, 4.4.14, 5.0.6, 6.1.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: ajv
  • Introduced through: gulp-eslint@4.0.2

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 ajv@5.5.2
    Remediation: Upgrade to gulp-eslint@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 table@4.0.2 ajv@5.5.2
    Remediation: Upgrade to gulp-eslint@5.0.0.

Overview

ajv is an Another JSON Schema Validator

Affected versions of this package are vulnerable to Prototype Pollution. A carefully crafted JSON schema could be provided that allows execution of other code by prototype pollution. (While untrusted schemas are recommended against, the worst case of an untrusted schema should be a denial of service, not execution of code.)

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade ajv to version 6.12.3 or higher.

References

high severity

Internal Property Tampering

  • Vulnerable module: bson
  • Introduced through: mongoose@4.13.21, acl@0.4.11 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 bson@1.0.9
    Remediation: Upgrade to mongoose@5.3.9.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 acl@0.4.11 mongodb@2.2.36 mongodb-core@2.1.20 bson@1.0.9
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 connect-mongo@1.3.2 mongodb@2.2.36 mongodb-core@2.1.20 bson@1.0.9
    Remediation: Upgrade to connect-mongo@3.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mongodb@2.2.34 mongodb-core@2.1.18 bson@1.0.9
    Remediation: Upgrade to mongoose@5.2.9.

…and 1 more

Overview

bson is a BSON Parser for node and browser.

Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype, leading to cases where an object is serialized as a document rather than the intended BSON type.

NOTE: This vulnerability has also been identified as: CVE-2019-2391

Remediation

Upgrade bson to version 1.1.4 or higher.

References

high severity

Internal Property Tampering

  • Vulnerable module: bson
  • Introduced through: mongoose@4.13.21, acl@0.4.11 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 bson@1.0.9
    Remediation: Upgrade to mongoose@5.3.9.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 acl@0.4.11 mongodb@2.2.36 mongodb-core@2.1.20 bson@1.0.9
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 connect-mongo@1.3.2 mongodb@2.2.36 mongodb-core@2.1.20 bson@1.0.9
    Remediation: Upgrade to connect-mongo@3.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mongodb@2.2.34 mongodb-core@2.1.18 bson@1.0.9
    Remediation: Upgrade to mongoose@5.2.9.

…and 1 more

Overview

bson is a BSON Parser for node and browser.

Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype, leading to cases where an object is serialized as a document rather than the intended BSON type.

NOTE: This vulnerability has also been identified as: CVE-2020-7610

Remediation

Upgrade bson to version 1.1.4 or higher.

References

high severity

Arbitrary Code Execution

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.3.0.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Arbitrary Code Execution. The package's lookup helper doesn't validate templates correctly, allowing attackers to submit templates that execute arbitrary JavaScript in the system.

PoC

    {{#with split as |a|}}
        {{pop (push "alert('Vulnerable Handlebars JS');")}}
        {{#with (concat (lookup join (slice 0 1)))}}
            {{#each (slice 2 3)}}
                {{#with (apply 0 a)}}
                    {{.}}
                {{/with}}
            {{/each}}
        {{/with}}
    {{/with}}
{{/with}}

Remediation

Upgrade handlebars to version 3.0.8, 4.5.3 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: mongoose
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21
    Remediation: Upgrade to mongoose@5.13.20.

Overview

mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.

Affected versions of this package are vulnerable to Prototype Pollution in document.js, via update functions such as findByIdAndUpdate(). This allows attackers to achieve remote code execution.

Note: Only applications using Express and EJS are vulnerable.

PoC


import { connect, model, Schema } from 'mongoose';

await connect('mongodb://127.0.0.1:27017/exploit');

const Example = model('Example', new Schema({ hello: String }));

const example = await new Example({ hello: 'world!' }).save();
await Example.findByIdAndUpdate(example._id, {
    $rename: {
        hello: '__proto__.polluted'
    }
});

// this is what causes the pollution
await Example.find();

const test = {};
console.log(test.polluted); // world!
console.log(Object.prototype); // [Object: null prototype] { polluted: 'world!' }

process.exit();

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mongoose to version 5.13.20, 6.11.3, 7.3.4 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: run-sequence@2.1.0, gulp-autoprefixer@4.0.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 run-sequence@2.1.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 run-sequence@2.1.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-rev@8.0.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 run-sequence@2.1.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-util@3.0.7 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 wiredep@4.0.0 wiredep-cli@0.1.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-rev@8.0.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 run-sequence@2.1.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-util@3.0.7 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 wiredep@4.0.0 wiredep-cli@0.1.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-concat@2.6.0 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-footer@1.0.5 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-header@1.8.2 gulp-util@3.0.8 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 babel-code-frame@6.26.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp-sass@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-concat@2.6.0 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-footer@1.0.5 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-header@1.8.2 gulp-util@3.0.8 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 babel-code-frame@6.26.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp-sass@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 wrap-ansi@2.1.0 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp-sass@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 wrap-ansi@2.1.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to gulp-sass@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 wrap-ansi@2.1.0 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 logalot@2.1.0 squeak@1.3.0 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 yargs@7.1.2 cliui@3.2.0 wrap-ansi@2.1.0 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1

…and 47 more

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]* and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*.

PoC

import ansiRegex from 'ansi-regex';

for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = "\u001B["+";".repeat(i*10000);
    ansiRegex().test(attack_str)
    var time_cost = Date.now() - time;
    console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ansi-regex to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: async
  • Introduced through: async@2.5.0 and mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 async@2.5.0
    Remediation: Upgrade to async@2.6.4.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 async@2.6.0
    Remediation: Upgrade to mongoose@5.7.3.

Overview

Affected versions of this package are vulnerable to Prototype Pollution via the mapValues() method, due to improper check in createObjectIterator function.

PoC

//when objects are parsed, all properties are created as own (the objects can come from outside sources (http requests/ file))
const hasOwn = JSON.parse('{"__proto__": {"isAdmin": true}}');

//does not have the property,  because it's inside object's own "__proto__"
console.log(hasOwn.isAdmin);

async.mapValues(hasOwn, (val, key, cb) => cb(null, val), (error, result) => {
  // after the method executes, hasOwn.__proto__ value (isAdmin: true) replaces the prototype of the newly created object, leading to potential exploits.
  console.log(result.isAdmin);
});

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade async to version 2.6.4, 3.2.2 or higher.

References

high severity

Excessive Platform Resource Consumption within a Loop

  • Vulnerable module: braces
  • Introduced through: gulp@4.0.2, gulp-nodemon@2.5.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 braces@2.3.2
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 braces@2.3.2
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 braces@2.3.2
    Remediation: Upgrade to gulp-imagemin@6.1.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to gulp-load-plugins@2.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 findup-sync@0.4.3 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to gulp-load-plugins@2.0.1.

…and 14 more

Overview

braces is a Bash-like brace expansion, implemented in JavaScript.

Affected versions of this package are vulnerable to Excessive Platform Resource Consumption within a Loop due improper limitation of the number of characters it can handle, through the parse function. An attacker can cause the application to allocate excessive memory and potentially crash by sending imbalanced braces as input.

PoC

const { braces } = require('micromatch');

console.log("Executing payloads...");

const maxRepeats = 10;

for (let repeats = 1; repeats <= maxRepeats; repeats += 1) {
  const payload = '{'.repeat(repeats*90000);

  console.log(`Testing with ${repeats} repeats...`);
  const startTime = Date.now();
  braces(payload);
  const endTime = Date.now();
  const executionTime = endTime - startTime;
  console.log(`Regex executed in ${executionTime / 1000}s.\n`);
} 

Remediation

Upgrade braces to version 3.0.3 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: dicer
  • Introduced through: multer@1.4.4

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 multer@1.4.4 busboy@0.2.14 dicer@0.2.5

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS). A malicious attacker can send a modified form to server, and crash the nodejs service. An attacker could sent the payload again and again so that the service continuously crashes.

PoC

await fetch('http://127.0.0.1:8000', { method: 'POST', headers: { ['content-type']: 'multipart/form-data; boundary=----WebKitFormBoundaryoo6vortfDzBsDiro', ['content-length']: '145', connection: 'keep-alive', }, body: '------WebKitFormBoundaryoo6vortfDzBsDiro\r\n Content-Disposition: form-data; name="bildbeschreibung"\r\n\r\n\r\n------WebKitFormBoundaryoo6vortfDzBsDiro--' });

Remediation

There is no fixed version for dicer.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.2.0.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Denial of Service (DoS). The package's parser may be forced into an endless loop while processing specially-crafted templates, which may allow attackers to exhaust system resources leading to Denial of Service.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade handlebars to version 4.4.5 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution through the zipObjectDeep function due to improper user input sanitization in the baseZipObject function.

PoC

lodash.zipobjectdeep:

const zipObjectDeep = require("lodash.zipobjectdeep");

let emptyObject = {};


console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined

zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function

console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true

lodash:

const test = require("lodash");

let emptyObject = {};


console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined

test.zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function

console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.17 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: merge
  • Introduced through: gulp-ng-annotate@2.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 merge@1.2.1

Overview

merge is a library that allows you to merge multiple objects into one, optionally creating a new cloned object. Similar to the jQuery.extend but more flexible. Works in Node.js and the browser.

Affected versions of this package are vulnerable to Prototype Pollution. The 'merge' function already checks for 'proto' keys in an object to prevent prototype pollution, but does not check for 'constructor' or 'prototype' keys.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade merge to version 2.1.0 or higher.

References

high severity

Inefficient Regular Expression Complexity

  • Vulnerable module: micromatch
  • Introduced through: gulp@4.0.2, gulp-nodemon@2.5.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10
    Remediation: Upgrade to gulp-imagemin@6.1.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 micromatch@2.3.11
    Remediation: Upgrade to gulp-load-plugins@2.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 findup-sync@0.4.3 micromatch@2.3.11
    Remediation: Upgrade to gulp-load-plugins@2.0.1.

…and 12 more

Overview

Affected versions of this package are vulnerable to Inefficient Regular Expression Complexity due to the use of unsafe pattern configurations that allow greedy matching through the micromatch.braces() function. An attacker can cause the application to hang or slow down by passing a malicious payload that triggers extensive backtracking in regular expression processing.

Remediation

Upgrade micromatch to version 4.0.8 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: mongodb
  • Introduced through: acl@0.4.11, connect-mongo@1.3.2 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 acl@0.4.11 mongodb@2.2.36
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 connect-mongo@1.3.2 mongodb@2.2.36
    Remediation: Upgrade to connect-mongo@3.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mongodb@2.2.34
    Remediation: Upgrade to mongoose@5.4.10.

Overview

mongodb is an official MongoDB driver for Node.js.

Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to properly catch an exception when a collection name is invalid and the DB does not exist, crashing the application.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade mongodb to version 3.1.13 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: mquery
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mquery@2.3.3
    Remediation: Upgrade to mongoose@5.12.3.

Overview

mquery is an Expressive query building for MongoDB

Affected versions of this package are vulnerable to Prototype Pollution via the mergeClone() function.

PoC by zhou, peng

mquery = require('mquery');
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mquery.utils.mergeClone({}, JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mquery to version 3.2.5 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-svgo@7.1.0 svgo@1.3.2 css-select@2.1.0 nth-check@1.0.2
    Remediation: Upgrade to gulp-imagemin@8.0.0.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when parsing crafted invalid CSS nth-checks, due to the sub-pattern \s*(?:([+-]?)\s*(\d+))? in RE_NTH_ELEMENT with quantified overlapping adjacency.

PoC

var nthCheck = require("nth-check")
for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = '2n' + ' '.repeat(i*10000)+"!";
    try {
        nthCheck.parse(attack_str) 
    }
    catch(err) {
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
    }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade nth-check to version 2.0.1 or higher.

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: gulp-refresh@1.1.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 body-parser@1.14.2 qs@5.2.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 qs@2.2.5

Overview

qs is a querystring parser that supports nesting and arrays, with a depth limit.

Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString(), hasOwnProperty(),etc.

From qs documentation:

By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.

Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.

In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [ or ]. e.g. qs.parse("]=toString") will return {toString = true}, as a result, calling toString() on the object will throw an exception.

Example:

qs.parse('toString=foo', { allowPrototypes: false })
// {}

qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten

For more information, you can check out our blog.

Disclosure Timeline

  • February 13th, 2017 - Reported the issue to package owner.
  • February 13th, 2017 - Issue acknowledged by package owner.
  • February 16th, 2017 - Partial fix released in versions 6.0.3, 6.1.1, 6.2.2, 6.3.1.
  • March 6th, 2017 - Final fix released in versions 6.4.0,6.3.2, 6.2.3, 6.1.2 and 6.0.4

Remediation

Upgrade qs to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.

References

high severity

Prototype Poisoning

  • Vulnerable module: qs
  • Introduced through: gulp-refresh@1.1.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 body-parser@1.14.2 qs@5.2.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 qs@2.2.5

Overview

qs is a querystring parser that supports nesting and arrays, with a depth limit.

Affected versions of this package are vulnerable to Prototype Poisoning which allows attackers to cause a Node process to hang, processing an Array object whose prototype has been replaced by one with an excessive length value.

Note: In many typical Express use cases, an unauthenticated remote attacker can place the attack payload in the query string of the URL that is used to visit the application, such as a[__proto__]=b&a[__proto__]&a[length]=100000000.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade qs to version 6.2.4, 6.3.3, 6.4.1, 6.5.3, 6.6.1, 6.7.3, 6.8.3, 6.9.7, 6.10.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: gulp-nodemon@2.5.0 and gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 nodemon@2.0.22 simple-update-notifier@1.1.0 semver@7.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 semver@5.3.0
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

semver is a semantic version parser used by npm.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range, when untrusted user data is provided as a range.

PoC


const semver = require('semver')
const lengths_2 = [2000, 4000, 8000, 16000, 32000, 64000, 128000]

console.log("n[+] Valid range - Test payloads")
for (let i = 0; i =1.2.3' + ' '.repeat(lengths_2[i]) + '<1.3.0';
const start = Date.now()
semver.validRange(value)
// semver.minVersion(value)
// semver.maxSatisfying(["1.2.3"], value)
// semver.minSatisfying(["1.2.3"], value)
// new semver.Range(value, {})

const end = Date.now();
console.log('length=%d, time=%d ms', value.length, end - start);
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver to version 5.7.2, 6.3.1, 7.5.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

…and 1 more

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). This can occur when running the regex on untrusted user input in a server context.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver-regex to version 4.0.1, 3.1.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

…and 1 more

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). semverRegex function contains a regex that allows exponential backtracking.

PoC

import semverRegex from 'semver-regex';

// The following payload would take excessive CPU cycles
var payload = '0.0.0-0' + '.-------'.repeat(100000) + '@';
semverRegex().test(payload);

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver-regex to version 3.1.3 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: trim-newlines
  • Introduced through: gulp-sass@3.2.1, gulp-angular-templatecache@2.0.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to gulp-sass@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-util@3.0.7 dateformat@1.0.12 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to gulp-angular-templatecache@2.1.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 logalot@2.1.0 squeak@1.3.0 lpad-align@1.1.2 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 logalot@2.1.0 squeak@1.3.0 lpad-align@1.1.2 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 logalot@2.1.0 squeak@1.3.0 lpad-align@1.1.2 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 logalot@2.1.0 squeak@1.3.0 lpad-align@1.1.2 meow@3.7.0 trim-newlines@1.0.0

…and 3 more

Overview

trim-newlines is a Trim newlines from the start and/or end of a string

Affected versions of this package are vulnerable to Denial of Service (DoS) via the end() method.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade trim-newlines to version 3.0.1, 4.0.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: unset-value
  • Introduced through: gulp@4.0.2, gulp-nodemon@2.5.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 anymatch@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 liftoff@3.1.0 findup-sync@3.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 gulp-cli@2.3.0 matchdep@2.0.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 unset-value@1.0.0

…and 64 more

Overview

Affected versions of this package are vulnerable to Prototype Pollution via the unset function in index.js, because it allows access to object prototype properties.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade unset-value to version 2.0.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.2.0.

Overview

handlebars is a extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. Templates may alter an Object's __proto__ and __defineGetter__ properties, which may allow an attacker to execute arbitrary code on the server through crafted payloads.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 4.3.0, 3.0.8 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep could be tricked into adding or modifying properties of Object.prototype using a constructor payload.

PoC by Snyk

const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'

function check() {
    mergeFn({}, JSON.parse(payload));
    if (({})[`a0`] === true) {
        console.log(`Vulnerable to Prototype Pollution via ${payload}`);
    }
  }

check();

For more information, check out our blog post

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.12 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution via the set and setwith functions due to improper user input sanitization.

PoC

lod = require('lodash')
lod.set({}, "__proto__[test2]", "456")
console.log(Object.prototype)

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.17 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: merge
  • Introduced through: gulp-ng-annotate@2.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 merge@1.2.1

Overview

merge is a library that allows you to merge multiple objects into one, optionally creating a new cloned object. Similar to the jQuery.extend but more flexible. Works in Node.js and the browser.

Affected versions of this package are vulnerable to Prototype Pollution via _recursiveMerge .

PoC:

const merge = require('merge');

const payload2 = JSON.parse('{"x": {"__proto__":{"polluted":"yes"}}}');

let obj1 = {x: {y:1}};

console.log("Before : " + obj1.polluted);
merge.recursive(obj1, payload2);
console.log("After : " + obj1.polluted);
console.log("After : " + {}.polluted);

Output:

Before : undefined
After : yes
After : yes

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade merge to version 2.1.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: mquery
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mquery@2.3.3
    Remediation: Upgrade to mongoose@5.11.7.

Overview

mquery is an Expressive query building for MongoDB

Affected versions of this package are vulnerable to Prototype Pollution via the merge function within lib/utils.js. Depending on if user input is provided, an attacker can overwrite and pollute the object prototype of a program.

PoC

   require('./env').getCollection(function(err, collection) {
      assert.ifError(err);
      col = collection;
      done();
    });
    var payload = JSON.parse('{"__proto__": {"polluted": "vulnerable"}}');
    var m = mquery(payload);
    console.log({}.polluted);
// The empty object {} will have a property called polluted which will print vulnerable

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mquery to version 3.2.3 or higher.

References

high severity

Code Injection

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Code Injection via template.

PoC

var _ = require('lodash');

_.template('', { variable: '){console.log(process.env)}; with(obj' })()

Remediation

Upgrade lodash to version 4.17.21 or higher.

References

high severity

Code Injection

  • Vulnerable module: lodash.template
  • Introduced through: gulp-autoprefixer@4.0.0, gulp-ng-annotate@2.0.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-rev@8.0.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 run-sequence@2.1.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-util@3.0.7 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-concat@2.6.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-footer@1.0.5 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-angular-templatecache@2.0.0 gulp-header@1.8.2 gulp-util@3.0.8 lodash.template@3.6.2

…and 7 more

Overview

lodash.template is a The Lodash method _.template exported as a Node.js module.

Affected versions of this package are vulnerable to Code Injection via template.

PoC

var _ = require('lodash');

_.template('', { variable: '){console.log(process.env)}; with(obj' })()

Remediation

There is no fixed version for lodash.template.

References

high severity

Remote Code Execution (RCE)

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.3.5.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Remote Code Execution (RCE) when selecting certain compiling options to compile templates coming from an untrusted source.

POC

<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script> 
<script> 
// compile the template 
var s = ` 
{{#with (__lookupGetter__ "__proto__")}} 
{{#with (./constructor.getOwnPropertyDescriptor . "valueOf")}} 
{{#with ../constructor.prototype}} 
{{../../constructor.defineProperty . "hasOwnProperty" ..}} 
{{/with}} 
{{/with}} 
{{/with}} 
{{#with "constructor"}} 
{{#with split}} 
{{pop (push "alert('Vulnerable Handlebars JS when compiling in strict mode');")}} 
{{#with .}} 
{{#with (concat (lookup join (slice 0 1)))}} 
{{#each (slice 2 3)}} 
{{#with (apply 0 ../..)}} 
{{.}} 
{{/with}} 
{{/each}} 
{{/with}} 
{{/with}} 
{{/with}} 
{{/with}} 
`;
var template = Handlebars.compile(s, { 
strict: true 
}); 
// execute the compiled template and print the output to the console console.log(template({})); 
</script>

Remediation

Upgrade handlebars to version 4.7.7 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: mongoose
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21
    Remediation: Upgrade to mongoose@5.13.15.

Overview

mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.

Affected versions of this package are vulnerable to Prototype Pollution in the Schema.path() function.

Note: CVE-2022-24304 is a duplicate of CVE-2022-2564.

PoC:

const mongoose = require('mongoose');
const schema = new mongoose.Schema();

malicious_payload = '__proto__.toString'

schema.path(malicious_payload, [String])

x = {}
console.log(x.toString())

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mongoose to version 5.13.15, 6.4.6 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.3.2.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. Prototype access to the template engine allows for potential code execution.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade handlebars to version 4.6.0 or higher.

References

medium severity

Denial of Service (DoS)

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Denial of Service (DoS). Uncontrolled recursion is possible in Sass::Complex_Selector::perform in ast.hpp and Sass::Inspect::operator in inspect.cpp. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

There is no fixed version for node-sass.

References

medium severity

Out-of-Bounds

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Out-of-Bounds. A heap-based buffer over-read exists in Sass::Prelexer::parenthese_scope in prelexer.hpp. node-sass is affected by this vulnerability due to its bundled usage of libsass.

Remediation

There is no fixed version for node-sass.

References

medium severity

Out-of-Bounds

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Out-of-Bounds via Sass::Prelexer::alternatives in prelexer.hpp. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

There is no fixed version for node-sass.

References

medium severity

Out-of-bounds Read

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Out-of-bounds Read. The function handle_error in sass_context.cpp allows attackers to cause a denial-of-service resulting from a heap-based buffer over-read via a crafted sass file. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

There is no fixed version for node-sass.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: request
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 request@2.88.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 request@2.88.2

Overview

request is a simplified http request client.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).

NOTE: request package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.

Remediation

A fix was pushed into the master branch but not yet published.

References

medium severity

Uncontrolled Resource Consumption ('Resource Exhaustion')

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Uncontrolled Resource Consumption ('Resource Exhaustion') due to the lack of folders count validation during the folder creation process. An attacker who generates a large number of sub-folders can consume memory on the system running the software and even crash the client within few seconds of running it using a path with too many sub-folders inside.

Remediation

Upgrade tar to version 6.2.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: tough-cookie
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 request@2.88.2 tough-cookie@2.5.0

Overview

tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.

Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.

PoC

// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
  "Slonser=polluted; Domain=__proto__; Path=/notauth",
  "https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
  "Auth=Lol; Domain=google.com; Path=/notauth",
  "https://google.com/"
);

//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade tough-cookie to version 4.1.3 or higher.

References

medium severity

Improper Input Validation

  • Vulnerable module: xmldom
  • Introduced through: passport-twitter@1.0.4

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.

Affected versions of this package are vulnerable to Improper Input Validation. It does not correctly escape special characters when serializing elements are removed from their ancestor. This may lead to unexpected syntactic changes during XML processing in some downstream applications.

Note: Customers who use "xmldom" package, should use "@xmldom/xmldom" instead, as "xmldom" is no longer maintained.

Remediation

There is no fixed version for xmldom.

References

medium severity

  • Vulnerable module: cookie
  • Introduced through: socket.io@2.5.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 socket.io@2.5.1 engine.io@3.6.2 cookie@0.4.2
    Remediation: Upgrade to socket.io@4.8.0.

Overview

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via the cookie name, path, or domain, which can be used to set unexpected values to other cookie fields.

Workaround

Users who are not able to upgrade to the fixed version should avoid passing untrusted or arbitrary values for the cookie fields and ensure they are set by the application instead of user input.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

Upgrade cookie to version 0.7.0 or higher.

References

medium severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress-tar
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1

…and 33 more

Overview

decompress-tar is a tar plugin for decompress.

Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip). It is possible to bypass the security measures provided by decompress and conduct ZIP path traversal through symlinks.

PoC

const decompress = require('decompress');

decompress('slip.tar.gz', 'dist').then(files => {
    console.log('done!');
});

Details

It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:


+2018-04-15 22:04:29 ..... 19 19 good.txt

+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys

Remediation

There is no fixed version for decompress-tar.

References

medium severity

HTTP Header Injection

  • Vulnerable module: nodemailer
  • Introduced through: nodemailer@4.0.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 nodemailer@4.0.1
    Remediation: Upgrade to nodemailer@6.6.1.

Overview

nodemailer is an Easy as cake e-mail sending from your Node.js applications

Affected versions of this package are vulnerable to HTTP Header Injection if unsanitized user input that may contain newlines and carriage returns is passed into an address object.

PoC:

const userEmail = 'foo@bar.comrnSubject: foobar'; // imagine this comes from e.g. HTTP request params or is otherwise user-controllable
await transporter.sendMail({
from: '...',
to: '...',
replyTo: {
name: 'Customer',
address: userEmail,
},
subject: 'My Subject',
text: message,
});

Remediation

Upgrade nodemailer to version 6.6.1 or higher.

References

medium severity

Missing Release of Resource after Effective Lifetime

  • Vulnerable module: inflight
  • Introduced through: glob@7.2.3, wiredep@4.0.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 wiredep@4.0.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 del@3.0.0 globby@6.1.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 del@3.0.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-less@4.0.1 accord@0.29.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 vinyl-fs@3.0.3 glob-stream@6.1.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 sass-graph@2.2.5 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 true-case-path@1.0.3 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 wiredep@4.0.0 wiredep-cli@0.1.0 wiredep@4.0.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 exec-buffer@3.2.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 exec-buffer@3.2.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 exec-buffer@3.2.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 vinyl-fs@3.0.3 glob-stream@6.1.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 gaze@1.1.3 globule@1.3.4 glob@7.1.7 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 fstream@1.0.12 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-eslint@4.0.2 eslint@4.19.1 file-entry-cache@2.0.0 flat-cache@1.3.4 rimraf@2.6.3 glob@7.2.3 inflight@1.0.6
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2 fstream@1.0.12 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6

…and 19 more

Overview

Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres function due to improperly deleting keys from the reqs object after execution of callbacks. This behavior causes the keys to remain in the reqs object, which leads to resource exhaustion.

Exploiting this vulnerability results in crashing the node process or in the application crash.

Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.

To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.

PoC

const inflight = require('inflight');

function testInflight() {
  let i = 0;
  function scheduleNext() {
    let key = `key-${i++}`;
    const callback = () => {
    };
    for (let j = 0; j < 1000000; j++) {
      inflight(key, callback);
    }

    setImmediate(scheduleNext);
  }


  if (i % 100 === 0) {
    console.log(process.memoryUsage());
  }

  scheduleNext();
}

testInflight();

Remediation

There is no fixed version for inflight.

References

medium severity

Cryptographic Backdoor

  • Vulnerable module: generate-password
  • Introduced through: generate-password@1.3.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 generate-password@1.3.0
    Remediation: Upgrade to generate-password@1.4.1.

Overview

generate-password is a relatively extensive library for generating random and unique passwords.

Affected versions of this package are vulnerable to Cryptographic Backdoor. It generates random values that are biased towards certain characters depending on the chosen character sets. This may result in guessable passwords.

Remediation

Upgrade generate-password to version 1.4.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2
    Remediation: Upgrade to express-hbs@2.3.5.

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution when selecting certain compiling options to compile templates coming from an untrusted source.

POC

<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script> 
<script> 
// compile the template 

var s2 = `{{'a/.") || alert("Vulnerable Handlebars JS when compiling in compat mode'}}`; 
var template = Handlebars.compile(s2, { 
compat: true 
}); 
// execute the compiled template and print the output to the console console.log(template({})); 
</script>

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 4.7.7 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: minimist
  • Introduced through: express-hbs@1.1.1 and gulp-ng-annotate@2.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2 optimist@0.6.1 minimist@0.0.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 ng-annotate@1.2.2 optimist@0.6.1 minimist@0.0.10

Overview

minimist is a parse argument options module.

Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype using a constructor or __proto__ payload.

PoC by Snyk

require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true

require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade minimist to version 0.2.1, 1.2.3 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: mongoose
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21
    Remediation: Upgrade to mongoose@5.12.2.

Overview

mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.

Affected versions of this package are vulnerable to Prototype Pollution. The mongoose.Schema() function is subject to prototype pollution due to the recursively calling of Schema.prototype.add() function to add new items into the schema object. This vulnerability allows modification of the Object prototype.

PoC

mongoose = require('mongoose');
mongoose.version; //'5.12.0'
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mongoose.Schema(JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mongoose to version 5.12.2 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: mpath
  • Introduced through: mongoose@4.13.21

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 mongoose@4.13.21 mpath@0.5.1
    Remediation: Upgrade to mongoose@5.13.9.

Overview

mpath is a package that gets/sets javascript object values using MongoDB-like path notation.

Affected versions of this package are vulnerable to Prototype Pollution. A type confusion vulnerability can lead to a bypass of CVE-2018-16490. In particular, the condition ignoreProperties.indexOf(parts[i]) !== -1 returns -1 if parts[i] is ['__proto__']. This is because the method that has been called if the input is an array is Array.prototype.indexOf() and not String.prototype.indexOf(). They behave differently depending on the type of the input.

PoC

const mpath = require('mpath');
// mpath.set(['__proto__', 'polluted'], 'yes', {});
// console.log(polluted); // ReferenceError: polluted is not defined

mpath.set([['__proto__'], 'polluted'], 'yes', {});
console.log(polluted); // yes

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade mpath to version 0.8.4 or higher.

References

medium severity

Information Exposure

  • Vulnerable module: express-hbs
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1
    Remediation: Upgrade to express-hbs@2.4.0.

Overview

express-hbs is an Express handlebars template engine complete with multiple layouts, partials and blocks.

Affected versions of this package are vulnerable to Information Exposure. The layout parameter may trigger file disclosure vulnerabilities in downstream applications. This potential vulnerability is somewhat restricted in that only files with existing extensions (i.e. file.extension) can be included, files that lack an extension will have .hbs appended to them.

Remediation

Upgrade express-hbs to version 2.4.0 or higher.

References

medium severity

Open Redirect

  • Vulnerable module: got
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-build@3.0.0 download@6.2.5 got@7.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-build@3.0.0 download@6.2.5 got@7.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-build@3.0.0 download@6.2.5 got@7.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-build@3.0.0 download@6.2.5 got@7.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2

…and 5 more

Overview

Affected versions of this package are vulnerable to Open Redirect due to missing verification of requested URLs. It allowed a victim to be redirected to a UNIX socket.

Remediation

Upgrade got to version 11.8.5, 12.1.0 or higher.

References

medium severity

XML External Entity (XXE) Injection

  • Vulnerable module: xmldom
  • Introduced through: passport-twitter@1.0.4

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.

Affected versions of this package are vulnerable to XML External Entity (XXE) Injection. Does not correctly preserve system identifiers, FPIs or namespaces when repeatedly parsing and serializing maliciously crafted documents.

Details

XXE Injection is a type of attack against an application that parses XML input. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By default, many XML processors allow specification of an external entity, a URI that is dereferenced and evaluated during XML processing. When an XML document is being parsed, the parser can make a request and include the content at the specified URI inside of the XML document.

Attacks can include disclosing local files, which may contain sensitive data such as passwords or private user data, using file: schemes or relative paths in the system identifier.

For example, below is a sample XML document, containing an XML element- username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
   <username>John</username>
</xml>

An external XML entity - xxe, is defined using a system identifier and present within a DOCTYPE header. These entities can access local or remote content. For example the below code contains an external XML entity that would fetch the content of /etc/passwd and display it to the user rendered by username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE foo [
   <!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
   <username>&xxe;</username>
</xml>

Other XXE Injection attacks can access local resources that may not stop returning data, possibly impacting application availability and leading to Denial of Service.

Remediation

Upgrade xmldom to version 0.5.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: browserslist
  • Introduced through: gulp-autoprefixer@4.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 autoprefixer@7.2.6 browserslist@2.11.3
    Remediation: Upgrade to gulp-autoprefixer@6.0.0.

Overview

browserslist is a Share target browsers between different front-end tools, like Autoprefixer, Stylelint and babel-env-preset

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) during parsing of queries.

PoC by Yeting Li

var browserslist = require("browserslist")
function build_attack(n) {
    var ret = "> "
    for (var i = 0; i < n; i++) {
        ret += "1"
    }
    return ret + "!";
}

// browserslist('> 1%')

//browserslist(build_attack(500000))
for(var i = 1; i <= 500000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            browserslist(attack_str);
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
        }
    }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade browserslist to version 4.16.5 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: gulp@4.0.2, gulp-nodemon@2.5.0 and others

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 glob-parent@3.1.0
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp@4.0.2 vinyl-fs@3.0.3 glob-stream@6.1.0 glob-parent@3.1.0
    Remediation: Upgrade to gulp@5.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 glob-watcher@5.0.5 chokidar@2.1.8 glob-parent@3.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-nodemon@2.5.0 gulp@4.0.2 vinyl-fs@3.0.3 glob-stream@6.1.0 glob-parent@3.1.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin@6.1.0 globby@8.0.2 fast-glob@2.2.7 glob-parent@3.1.0
    Remediation: Upgrade to gulp-imagemin@6.1.0.

…and 2 more

Overview

glob-parent is a package that helps extracting the non-magic parent path from a glob string.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure regex used to check for strings ending in enclosure containing path separator.

PoC by Yeting Li

var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}

return ret;
}

globParent(build_attack(5000));

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade glob-parent to version 5.1.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: http-cache-semantics
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2 cacheable-request@2.1.4 http-cache-semantics@3.8.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2 cacheable-request@2.1.4 http-cache-semantics@3.8.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2 cacheable-request@2.1.4 http-cache-semantics@3.8.1
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 download@7.1.0 got@8.3.2 cacheable-request@2.1.4 http-cache-semantics@3.8.1

…and 1 more

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The issue can be exploited via malicious request header values sent to a server, when that server reads the cache policy from the request using this library.

PoC

Run the following script in Node.js after installing the http-cache-semantics NPM package:

const CachePolicy = require("http-cache-semantics");

for (let i = 0; i <= 5; i++) {

const attack = "a" + " ".repeat(i * 7000) +
"z";

const start = performance.now();
new CachePolicy({
headers: {},
}, {
headers: {
"cache-control": attack,
},


});
console.log(`${attack.length}: ${performance.now() - start}ms`);
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade http-cache-semantics to version 4.1.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: js-beautify
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 js-beautify@1.6.8
    Remediation: Upgrade to express-hbs@2.3.2.

Overview

js-beautify is a reformat and re-indent bookmarklets, ugly JavaScript, unpack scripts packed by Dean Edward’s popular packer, as well as partly deobfuscate scripts processed by the npm package "javascript-obfuscator".

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an unsafe regex in tokenizer.py and tokenizer.js.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade js-beautify to version 1.14.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: express-hbs@1.1.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 lodash@4.17.11
    Remediation: Upgrade to express-hbs@2.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber, trim and trimEnd functions.

POC

var lo = require('lodash');

function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}

return ret + "1";
}

var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)

var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)

var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade lodash to version 4.17.21 or higher.

References

medium severity

Improper Certificate Validation

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Improper Certificate Validation. Certificate validation is disabled by default when requesting binaries, even if the user is not specifying an alternative download path.

Remediation

Upgrade node-sass to version 7.0.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nodemailer
  • Introduced through: nodemailer@4.0.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 nodemailer@4.0.1
    Remediation: Upgrade to nodemailer@6.9.9.

Overview

nodemailer is an Easy as cake e-mail sending from your Node.js applications

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the attachDataUrls parameter or when parsing attachments with an embedded file. An attacker can exploit this vulnerability by sending a specially crafted email that triggers inefficient regular expression evaluation, leading to excessive consumption of CPU resources.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade nodemailer to version 6.9.9 or higher.

References

medium severity

Improper Input Validation

  • Vulnerable module: postcss
  • Introduced through: gulp-autoprefixer@4.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 postcss@6.0.23
    Remediation: Upgrade to gulp-autoprefixer@8.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 autoprefixer@7.2.6 postcss@6.0.23

Overview

postcss is a PostCSS is a tool for transforming styles with JS plugins.

Affected versions of this package are vulnerable to Improper Input Validation when parsing external Cascading Style Sheets (CSS) with linters using PostCSS. An attacker can cause discrepancies by injecting malicious CSS rules, such as @font-face{ font:(\r/*);}. This vulnerability is because of an insecure regular expression usage in the RE_BAD_BRACKET variable.

Remediation

Upgrade postcss to version 8.4.31 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: postcss
  • Introduced through: gulp-autoprefixer@4.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 postcss@6.0.23
    Remediation: Upgrade to gulp-autoprefixer@6.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-autoprefixer@4.0.0 autoprefixer@7.2.6 postcss@6.0.23
    Remediation: Upgrade to gulp-autoprefixer@6.0.0.

Overview

postcss is a PostCSS is a tool for transforming styles with JS plugins.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via getAnnotationURL() and loadAnnotation() in lib/previous-map.js. The vulnerable regexes are caused mainly by the sub-pattern \/\*\s*# sourceMappingURL=(.*).

PoC

var postcss = require("postcss")
function build_attack(n) {
    var ret = "a{}"
    for (var i = 0; i < n; i++) {
        ret += "/*# sourceMappingURL="
    }
    return ret + "!";
}

// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            postcss.parse(attack_str)
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
        }
    }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade postcss to version 8.2.13, 7.0.36 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: redis
  • Introduced through: acl@0.4.11

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 acl@0.4.11 redis@2.8.0

Overview

redis is an A high performance Redis client.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When a client is in monitoring mode, monitor_regex, which is used to detected monitor messages` could cause exponential backtracking on some strings, leading to denial of service.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade redis to version 3.1.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: scss-tokenizer
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 sass-graph@2.2.5 scss-tokenizer@0.2.3
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the loadAnnotation() function, due to the usage of insecure regex.

PoC

var scss = require("scss-tokenizer")
function build_attack(n) {
    var ret = "a{}"
    for (var i = 0; i < n; i++) {
        ret += "/*# sourceMappingURL="
    }
    return ret + "!";
}

// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            scss.tokenize(attack_str)
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
        }
    }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade scss-tokenizer to version 0.4.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

…and 1 more

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to improper usage of regex in the semverRegex() function.

PoC

'0.0.1-' + '-.--'.repeat(i) + ' '

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver-regex to version 3.1.4, 4.0.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: uglify-js
  • Introduced through: gulp-less@4.0.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-less@4.0.1 accord@0.29.0 uglify-js@2.8.29
    Remediation: Upgrade to gulp-less@5.0.0.

Overview

uglify-js is a JavaScript parser, minifier, compressor and beautifier toolkit.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the string_template and the decode_template functions.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade uglify-js to version 3.14.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@9.4.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 validator@9.4.1
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isSlug function

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "111"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }

    return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isSlug(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@9.4.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 validator@9.4.1
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isHSL function.

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "hsla(0"
    for (var i = 0; i < n; i++) {
        ret += " "
    }

    return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isHSL(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@9.4.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 validator@9.4.1
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isEmail function.

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = ""
    for (var i = 0; i < n; i++) {
        ret += "<"
    }

    return ret+"";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        validator.isEmail(attack_str,{ allow_display_name: true })
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Session Fixation

  • Vulnerable module: passport
  • Introduced through: passport@0.3.2

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 passport@0.3.2
    Remediation: Upgrade to passport@0.6.0.

Overview

passport is a Simple, unobtrusive authentication for Node.js.

Affected versions of this package are vulnerable to Session Fixation. When a user logs in or logs out, the session is regenerated instead of being closed.

Remediation

Upgrade passport to version 0.6.0 or higher.

References

medium severity

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to NULL Pointer Dereference via Sass::Parser::parseCompoundSelectorin parser_selectors.cpp. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Remediation

There is no fixed version for node-sass.

References

medium severity

Out-of-bounds Read

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Out-of-bounds Read via Sass::weaveParents in ast_sel_weave.cpp. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

There is no fixed version for node-sass.

References

medium severity

Uncontrolled Recursion

  • Vulnerable module: node-sass
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1

Overview

node-sass is a Node.js bindings package for libsass.

Affected versions of this package are vulnerable to Uncontrolled Recursion via Sass::Eval::operator()(Sass::Binary_Expression*) in eval.cpp. Note: node-sass is affected by this vulnerability due to its bundled usage of the libsass package.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

There is no fixed version for node-sass.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: imagemin-pngquant@6.0.1 and gulp-imagemin@5.0.3

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 imagemin-pngquant@6.0.1 pngquant-bin@5.0.2 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-gifsicle@6.0.1 gifsicle@4.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-jpegtran@6.0.0 jpegtran-bin@4.0.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-imagemin@5.0.3 imagemin-optipng@6.0.0 optipng-bin@5.1.0 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

…and 1 more

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).

PoC


// import of the vulnerable library
const semverRegex = require('semver-regex');
// import of measurement tools
const { PerformanceObserver, performance } = require('perf_hooks');

// config of measurements tools
const obs = new PerformanceObserver((items) => {
 console.log(items.getEntries()[0].duration);
 performance.clearMarks();
});
obs.observe({ entryTypes: ['measure'] });

// base version string
let version = "v1.1.3-0a"

// Adding the evil code, resulting in string
// v1.1.3-0aa.aa.aa.aa.aa.aa.a…a.a"
for(let i=0; i < 20; i++) {
   version += "a.a"
}

// produce a good version
// Parses well for the regex in milliseconds
let goodVersion = version + "2"

// good version proof
performance.mark("good before")
const goodresult = semverRegex().test(goodVersion);
performance.mark("good after")


console.log(`Good result: ${goodresult}`)
performance.measure('Good', 'good before', 'good after');

// create a bad/exploit version that is invalid due to the last $ sign
// will cause the nodejs engine to hang, if not, increase the a.a
// additions above a bit.
badVersion = version + "aaaaaaa$"

// exploit proof
performance.mark("bad before")
const badresult = semverRegex().test(badVersion);
performance.mark("bad after")

console.log(`Bad result: ${badresult}`)
performance.measure('Bad', 'bad before', 'bad after');

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver-regex to version 3.1.2 or higher.

References

medium severity
new

MPL-2.0 license

  • Module: mdn-data
  • Introduced through: gulp-csso@3.0.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-csso@3.0.1 csso@3.5.1 css-tree@1.0.0-alpha.29 mdn-data@1.1.4

MPL-2.0 license

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: braces
  • Introduced through: gulp-load-plugins@1.5.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to gulp-load-plugins@1.6.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-load-plugins@1.5.0 findup-sync@0.4.3 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to gulp-load-plugins@1.6.0.

Overview

braces is a Bash-like brace expansion, implemented in JavaScript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.

Disclosure Timeline

  • Feb 15th, 2018 - Initial Disclosure to package owner
  • Feb 16th, 2018 - Initial Response from package owner
  • Feb 18th, 2018 - Fix issued
  • Feb 19th, 2018 - Vulnerability published

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade braces to version 2.3.1 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: debug
  • Introduced through: gulp-refresh@1.1.0 and socket.io@2.5.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 body-parser@1.14.2 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 socket.io@2.5.1 debug@4.1.1
    Remediation: Upgrade to socket.io@3.0.5.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 socket.io@2.5.1 engine.io@3.6.2 debug@4.1.1
    Remediation: Upgrade to socket.io@3.0.0.
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 socket.io@2.5.1 socket.io-parser@3.4.3 debug@4.1.1
    Remediation: Upgrade to socket.io@3.0.0.

…and 1 more

Overview

debug is a small debugging utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors via manipulation of the str argument. The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.

Note: CVE-2017-20165 is a duplicate of this vulnerability.

PoC

Use the following regex in the %o formatter.

/\s*\n\s*/

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade debug to version 2.6.9, 3.1.0, 3.2.7, 4.3.1 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: jasmine-core
  • Introduced through: jasmine-core@3.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 jasmine-core@3.0.0
    Remediation: Upgrade to jasmine-core@3.1.0.

Overview

jasmine-core is a Behavior Driven Development testing framework for JavaScript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\s*function\s*(\w*)\s*\() in order to parse JS toString output on a function to get a function name. This can cause an impact of about 10 seconds matching time for data 64K characters long.

Disclosure Timeline

  • Feb 15th, 2018 - Initial Disclosure to package owner
  • Feb 15th, 2018 - Initial Response from package owner
  • Feb 15th, 2018 - Fix issued, not yet published to npm.
  • Feb 18th, 2018 - Vulnerability published
  • Mar 1st, 2018 - Fix published to npm.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade jasmine-core to version 3.1.0 or higher.

References

low severity

Prototype Pollution

  • Vulnerable module: minimist
  • Introduced through: express-hbs@1.1.1 and gulp-ng-annotate@2.0.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 express-hbs@1.1.1 handlebars@4.1.2 optimist@0.6.1 minimist@0.0.10
  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-ng-annotate@2.0.0 ng-annotate@1.2.2 optimist@0.6.1 minimist@0.0.10

Overview

minimist is a parse argument options module.

Affected versions of this package are vulnerable to Prototype Pollution due to a missing handler to Function.prototype.

Notes:

  • This vulnerability is a bypass to CVE-2020-7598

  • The reason for the different CVSS between CVE-2021-44906 to CVE-2020-7598, is that CVE-2020-7598 can pollute objects, while CVE-2021-44906 can pollute only function.

PoC by Snyk

require('minimist')('--_.constructor.constructor.prototype.foo bar'.split(' '));
console.log((function(){}).foo); // bar

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade minimist to version 0.2.4, 1.2.6 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ms
  • Introduced through: gulp-refresh@1.1.0

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-refresh@1.1.0 mini-lr@0.1.9 body-parser@1.14.2 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.

Overview

ms is a tiny millisecond conversion utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms() function.

Proof of concept

ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s

Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.

For more information on Regular Expression Denial of Service (ReDoS) attacks, go to our blog.

Disclosure Timeline

  • Feb 9th, 2017 - Reported the issue to package owner.
  • Feb 11th, 2017 - Issue acknowledged by package owner.
  • April 12th, 2017 - Fix PR opened by Snyk Security Team.
  • May 15th, 2017 - Vulnerability published.
  • May 16th, 2017 - Issue fixed and version 2.0.0 released.
  • May 21th, 2017 - Patches released for versions >=0.7.1, <=1.0.0.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ms to version 2.0.0 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tar
  • Introduced through: gulp-sass@3.2.1

Detailed paths

  • Introduced through: meanjs@meanjs/mean#ed8d04c4cacf305c25a7a13fface589fd80d1d58 gulp-sass@3.2.1 node-sass@4.14.1 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to gulp-sass@5.0.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When stripping the trailing slash from files arguments, the f.replace(/\/+$/, '') performance of this function can exponentially degrade when f contains many / characters resulting in ReDoS.

This vulnerability is not likely to be exploitable as it requires that the untrusted input is being passed into the tar.extract() or tar.list() array of entries to parse/extract, which would be unusual.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade tar to version 6.1.4, 5.0.8, 4.4.16 or higher.

References