diamonds@0.0.9-q

Vulnerabilities

76 via 371 paths

Dependencies

1946

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 3
  • 34
  • 34
  • 5
Status
  • 76
  • 0
  • 0

critical severity

Arbitrary Code Injection

  • Vulnerable module: growl
  • Introduced through: compound@1.2.4

Detailed paths

  • Introduced through: diamonds@0.0.9-q compound@1.2.4 kontroller@0.0.15 mocha@1.17.1 growl@1.7.0

Overview

growl is a package adding Growl support for Nodejs.

Affected versions of this package are vulnerable to Arbitrary Code Injection due to unsafe use of the eval() function. Node.js provides the eval() function by default, and is used to translate strings into Javascript code. An attacker can craft a malicious payload to inject arbitrary commands.

Remediation

Upgrade growl to version 1.10.0 or higher.

References

critical severity

Command Injection

  • Vulnerable module: launchpad
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 wct-local@2.1.5 launchpad@0.7.5

Overview

launchpad is a You can launch browsers! From NodeJS! Local ones! Remote ones! Browserstack ones!

Affected versions of this package are vulnerable to Command Injection via stop.

Remediation

There is no fixed version for launchpad.

References

critical severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution in zipObjectDeep due to an incomplete fix for CVE-2020-8203.

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 lodash to version 4.17.20 or higher.

References

high severity

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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

Out-of-bounds Read

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

Overview

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

Affected versions of this package are vulnerable to Out-of-bounds Read via the function Sass::Prelexer::exactly() which could be leveraged by an attacker to disclose information or manipulated to read from unmapped memory causing a denial of service. 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

Out-of-bounds Read

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

Overview

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

Affected versions of this package are vulnerable to Out-of-bounds Read via the function Sass::handle_error which could be leveraged by an attacker to disclose information or manipulated to read from unmapped memory causing a denial of service. 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

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

Overview

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

Affected versions of this package are vulnerable to Arbitrary File Overwrite. Extracting tarballs containing a hard-link to a file that already exists in the system, and a file that matches the hard-link may overwrite system's files with the contents of the extracted file.

Remediation

Upgrade tar to version 2.2.2, 4.4.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: yo@4.3.0, web-component-tester@6.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q yo@4.3.0 string-length@2.0.0 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 inquirer@6.5.2 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yosay@2.0.2 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 update-notifier@2.5.0 boxen@1.3.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 update-notifier@2.5.0 boxen@1.3.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 insight@0.10.3 inquirer@6.5.2 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 inquirer@5.2.0 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yeoman-environment@3.8.1 npmlog@5.0.1 gauge@3.0.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 inquirer@5.2.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 update-notifier@2.5.0 boxen@1.3.0 ansi-align@2.0.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 update-notifier@2.5.0 boxen@1.3.0 ansi-align@2.0.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 update-notifier@2.5.0 boxen@1.3.0 widest-line@2.0.1 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 update-notifier@2.5.0 boxen@1.3.0 widest-line@2.0.1 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yeoman-environment@3.8.1 npmlog@5.0.1 gauge@3.0.1 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 sw-precache@5.2.1 update-notifier@2.5.0 boxen@1.3.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 sw-precache@5.2.1 update-notifier@2.5.0 boxen@1.3.0 ansi-align@2.0.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 sw-precache@5.2.1 update-notifier@2.5.0 boxen@1.3.0 widest-line@2.0.1 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 inquirer@6.5.2 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q yo@4.3.0 insight@0.10.3 inquirer@6.5.2 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1 sass-graph@2.2.5 yargs@13.3.2 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1 sass-graph@2.2.5 yargs@13.3.2 cliui@5.0.0 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1 sass-graph@2.2.5 yargs@13.3.2 cliui@5.0.0 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1 sass-graph@2.2.5 yargs@13.3.2 cliui@5.0.0 wrap-ansi@5.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1 sass-graph@2.2.5 yargs@13.3.2 cliui@5.0.0 wrap-ansi@5.1.0 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0

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 6.0.1, 5.0.1 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 socket.io@2.4.1 engine.io@3.5.0

Overview

engine.io is a realtime engine behind Socket.IO. It provides the foundation of a bidirectional connection between client and server

Affected versions of this package are vulnerable to Denial of Service (DoS) via a POST request to the long polling transport.

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 engine.io to version 4.0.0 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: generator-angular@0.16.0, compound@1.2.4 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 minimatch@0.2.14
  • Introduced through: diamonds@0.0.9-q compound@1.2.4 kontroller@0.0.15 mocha@1.17.1 glob@3.2.3 minimatch@0.2.14
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 glob@4.5.3 minimatch@2.0.10
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 glob@4.5.3 minimatch@2.0.10
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 minimatch@2.0.10
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 glob@4.5.3 minimatch@2.0.10
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 findup-sync@0.2.1 glob@4.3.5 minimatch@2.0.10
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 glob@3.2.11 minimatch@0.3.0
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 glob@3.2.11 minimatch@0.3.0
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via complicated and illegal regexes.

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 minimatch to version 3.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: generator-angular@0.16.0, compound@1.2.4 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 minimatch@0.2.14
    Remediation: Open PR to patch minimatch@0.2.14.
  • Introduced through: diamonds@0.0.9-q compound@1.2.4 kontroller@0.0.15 mocha@1.17.1 glob@3.2.3 minimatch@0.2.14
    Remediation: Open PR to patch minimatch@0.2.14.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 glob@4.5.3 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 glob@4.5.3 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 glob@4.5.3 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 findup-sync@0.2.1 glob@4.3.5 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).

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 minimatch to version 3.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: mocha
  • Introduced through: compound@1.2.4

Detailed paths

  • Introduced through: diamonds@0.0.9-q compound@1.2.4 kontroller@0.0.15 mocha@1.17.1

Overview

mocha is a javascript test framework for node.js & the browser.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If the stack trace in utils.js begins with a large error message (>= 20k characters), and full-trace is not undisabled, utils.stackTraceFilter() will take exponential time to run.

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 mocha to version 6.0.0 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: mout
  • Introduced through: generator-angular@0.16.0 and web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 bower-config@0.5.3 mout@0.9.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 bower-config@1.4.3 mout@1.2.3
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 bower-config@1.4.3 mout@1.2.3

Overview

mout is a Modular Utilities

Affected versions of this package are vulnerable to Prototype Pollution. The deepFillIn function can be used to 'fill missing properties recursively', while the deepMixIn 'mixes objects into the target object, recursively mixing existing child objects as well'. In both cases, the key used to access the target object recursively is not checked, leading to a Prototype Pollution.

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

There is no fixed version for mout.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 nth-check@1.0.2
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 nth-check@1.0.2

Overview

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

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

Denial of Service (DoS)

  • Vulnerable module: qs
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 qs@0.6.6
    Remediation: Open PR to patch qs@0.6.6.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). During parsing, the qs module may create a sparse area (an array where no elements are filled), and grow that array to the necessary size based on the indices used on it. An attacker can specify a high index value in a query string, thus making the server allocate a respectively big array. Truly large values can cause the server to run out of memory and cause it to crash - thus enabling a Denial-of-Service attack.

Remediation

Upgrade qs to version 1.0.0 or higher.

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

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 qs@0.6.6

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

  • GitHub Commit
  • GitHub Issue

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: yo@4.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yeoman-doctor@5.0.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

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: yo@4.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yeoman-doctor@5.0.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

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

Symlink File Overwrite

  • Vulnerable module: tar
  • Introduced through: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
    Remediation: Open PR to patch tar@0.1.20.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
    Remediation: Open PR to patch tar@1.0.3.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
    Remediation: Open PR to patch tar@1.0.3.
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3
    Remediation: Open PR to patch tar@1.0.3.

Overview

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

Affected versions of this package are vulnerable to Symlink File Overwrite. It does not properly normalize symbolic links pointing to targets outside the extraction root. As a result, packages may hold symbolic links to parent and sibling directories and overwrite those files when the package is extracted.

Remediation

Upgrade tar to version 2.0.0 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tough-cookie
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 tough-cookie@0.9.15

Overview

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

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can provide a cookie, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).

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 tough-cookie to version 2.3.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: trim-newlines
  • Introduced through: yo@4.3.0, generator-polymer@1.3.0 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q yo@4.3.0 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 dateformat@1.0.12 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 github-username@2.1.0 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 pretty-bytes@2.0.1 meow@3.7.0 trim-newlines@1.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 sw-precache@5.2.1 meow@3.7.0 trim-newlines@1.0.0

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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: underscore.string
  • Introduced through: generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 underscore.string@3.3.5

Overview

underscore.string is a Javascript lacks complete string manipulation operations.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.

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 underscore.string.

References

high severity

Directory Traversal

  • Vulnerable module: adm-zip
  • Introduced through: web-component-tester@6.9.2, generator-angular@0.16.0 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 wct-sauce@2.1.0 sauce-connect-launcher@1.3.2 adm-zip@0.4.16
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 adm-zip@0.4.16
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-unzip@1.0.0 adm-zip@0.4.16

Overview

adm-zip is a JavaScript implementation for zip data compression for NodeJS.

Affected versions of this package are vulnerable to Directory Traversal. It could extract files outside the target folder.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

  • Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

  • Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside 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 malicious 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

Upgrade adm-zip to version 0.5.2 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: deep-extend
  • Introduced through: generator-famous@0.9.2 and generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 famous-metrics@0.2.0 rc@0.6.0 deep-extend@0.2.11
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 mem-fs-editor@2.3.0 deep-extend@0.4.2

Overview

deep-extend is a library for Recursive object extending.

Affected versions of this package are vulnerable to Prototype Pollution. Utilities function in all the listed modules can be tricked into modifying the prototype of "Object" when the attacker control part of the structure passed to these function. This can let an attacker add or modify existing property that will exist on all object.

PoC by HoLyVieR

var merge = require('deep-extend');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

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 deep-extend to version 0.5.1 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: fstream
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20 fstream@0.1.31

Overview

fstream is a package that supports advanced FS Streaming for Node.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. Extracting tarballs containing a hardlink to a file that already exists in the system and a file that matches the hardlink will overwrite the system's file with the contents of the extracted file.

Remediation

Upgrade fstream to version 1.0.12 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

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

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: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution via the setWith and set functions.

PoC by awarau

  • Create a JS file with this contents:
    lod = require('lodash')
    lod.setWith({}, "__proto__[test]", "123")
    lod.set({}, "__proto__[test2]", "456")
    console.log(Object.prototype)
    
  • Execute it with node
  • Observe that test and test2 is now in the 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

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: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution. The functions merge, mergeWith, and defaultsDeep could be tricked into adding or modifying properties of Object.prototype. This is due to an incomplete fix to CVE-2018-3721.

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 lodash to version 4.17.11 or higher.

References

high severity

Command Injection

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

Overview

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

Affected versions of this package are vulnerable to Command 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

Command Injection

  • Vulnerable module: lodash.template
  • Introduced through: generator-polymer@1.3.0 and web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 gulp-util@3.0.8 lodash.template@3.6.2
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 sw-precache@5.2.1 lodash.template@4.5.0

Overview

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

Affected versions of this package are vulnerable to Command 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: plist
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 wct-local@2.1.5 launchpad@0.7.5 plist@2.1.0

Overview

plist is a Mac OS X Plist parser/builder for Node.js and browsers

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks due to bundling a vulnerable version of the XMLBuilder package. This can cause an impact of about 10 seconds matching time for data 60 characters long.

Disclosure Timeline

  • Feb 5th, 2018 - Initial Disclosure to package owner
  • Feb 6th, 2018 - Initial Response from package owner
  • Mar 18th, 2018 - Fix issued
  • Apr 15th, 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 plist to version 3.0.1 or higher.

References

medium severity

Timing Attack

  • Vulnerable module: http-signature
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 http-signature@0.10.1
    Remediation: Open PR to patch http-signature@0.10.1.

Overview

http-signature is a reference implementation of Joyent's HTTP Signature scheme.

Affected versions of the package are vulnerable to Timing Attacks due to time-variable comparison of signatures.

The library implemented a character to character comparison, similar to the built-in string comparison mechanism, ===, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the signature are incorrect. An attacker can use this difference to perform a timing attack, essentially allowing them to guess the signature one character at a time.

You can read more about timing attacks in Node.js on the Snyk blog.

Remediation

Upgrade http-signature to version 1.0.0 or higher.

References

medium severity

Denial of Service (DoS)

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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

Denial of Service (DoS)

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). The parsing component allows attackers to cause uncontrolled recursion in Sass::Parser::parse_css_variable_value in parser.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

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

Overview

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

Affected versions of this package are vulnerable to NULL Pointer Dereference. In LibSass 3.5.5, a NULL Pointer Dereference in the function Sass::Eval::operator()``(Sass::Supports_Operator*) in eval.cpp may cause a Denial of Service (application crash) via a crafted sass input file.

Remediation

There is no fixed version for node-sass.

References

medium severity

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

Overview

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

Affected versions of this package are vulnerable to NULL Pointer Dereference. The function Sass::Selector_List::populate_extends in SharedPtr.hpp (used by ast.cpp and ast_selectors.cpp) may cause a Denial of Service (application crash) via a crafted sass input 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

Out-of-Bounds

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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::Prelexer::skip_over_scopes in prelexer.hpp when called from Sass::Parser::parse_import(), a similar issue to CVE-2018-11693. 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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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

Denial of Service (DoS)

  • Vulnerable module: qs
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 qs@0.6.6
    Remediation: Open PR to patch qs@0.6.6.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). When parsing a string representing a deeply nested object, qs will block the event loop for long periods of time. Such a delay may hold up the server's resources, keeping it from processing other requests in the meantime, thus enabling a Denial-of-Service attack.

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 qs to version 1.0.0 or higher.

References

medium severity

Improper Input Validation

  • Vulnerable module: xmldom
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 wct-local@2.1.5 launchpad@0.7.5 plist@2.1.0 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 removed from their ancestor. This may lead to unexpected syntactic changes during XML processing in some downstream applications.

Remediation

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

References

medium severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0

Overview

decompress is a package that can be used for extracting archives.

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

Upgrade decompress to version 4.2.1 or higher.

References

medium severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress-tar
  • Introduced through: generator-famous@0.9.2 and generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 decompress-tar@3.1.0

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

Prototype Pollution

  • Vulnerable module: hoek
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 hawk@1.0.0 hoek@0.9.1
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 hawk@1.0.0 boom@0.4.2 hoek@0.9.1
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 hawk@1.0.0 sntp@0.2.4 hoek@0.9.1
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 hawk@1.0.0 cryptiles@0.2.2 boom@0.4.2 hoek@0.9.1

Overview

hoek is an Utility methods for the hapi ecosystem.

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

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 hoek to version 4.2.1, 5.0.3 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

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

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 4.17.16 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

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 lodash to version 4.17.5 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tough-cookie
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 tough-cookie@0.9.15

Overview

tough-cookie is RFC6265 Cookies and Cookie Jar for node.js.

Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted cookie, causing the server to hang.

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 to version 2.3.3 or newer.

References

medium severity

Prototype Pollution

  • Vulnerable module: minimist
  • Introduced through: optimist@0.6.1, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q optimist@0.6.1 minimist@0.0.10
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 famous-metrics@0.2.0 rc@0.6.0 minimist@0.0.10
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 bower-config@0.5.3 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

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: set-getter
  • Introduced through: generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 npm-api@1.0.1 download-stats@0.3.4 lazy-cache@2.0.2 set-getter@0.1.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 npm-api@1.0.1 download-stats@0.3.4 lazy-cache@2.0.2 set-getter@0.1.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 npm-api@1.0.1 download-stats@0.3.4 lazy-cache@2.0.2 set-getter@0.1.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 npm-api@1.0.1 download-stats@0.3.4 lazy-cache@2.0.2 set-getter@0.1.1

Overview

set-getter is a Create nested getter properties and any intermediary dot notation ('a.b.c') paths

Affected versions of this package are vulnerable to Prototype Pollution. Allows an attacker to cause a denial of service and may lead to remote code execution.

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

There is no fixed version for set-getter.

References

medium severity

Arbitrary Code Injection

  • Vulnerable module: underscore
  • Introduced through: generator-angular@0.16.0 and web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 cheerio@0.13.1 underscore@1.5.2
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 nomnom@1.8.1 underscore@1.6.0

Overview

underscore is a JavaScript's functional programming helper library.

Affected versions of this package are vulnerable to Arbitrary Code Injection via the template function, particularly when the variable option is taken from _.templateSettings as it is not sanitized.

PoC

const _ = require('underscore');
_.templateSettings.variable = "a = this.process.mainModule.require('child_process').execSync('touch HELLO')";
const t = _.template("")();

Remediation

Upgrade underscore to version 1.13.0-2, 1.12.1 or higher.

References

medium severity

XML External Entity (XXE) Injection

  • Vulnerable module: xmldom
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 wct-local@2.1.5 launchpad@0.7.5 plist@2.1.0 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 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 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: css-what
  • Introduced through: generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 css-what@1.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 css-select@1.0.0 css-what@1.0.0

Overview

css-what is an a CSS selector parser

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via attribute parsing.

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 css-what to version 5.0.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: generator-polymer@1.3.0 and web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 vinyl-fs@2.4.4 glob-stream@5.3.5 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 globby@8.0.2 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 globby@8.0.2 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 globby@8.0.2 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 mem-fs-editor@7.1.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 globby@8.0.2 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 mem-fs-editor@7.1.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 globby@9.2.0 fast-glob@2.2.7 glob-parent@3.1.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 http-proxy-middleware@0.17.4 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0

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: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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

There is no fixed version for node-sass.

References

medium severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: uglify-js
  • Introduced through: web-component-tester@6.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 html-minifier@3.5.21 uglify-js@3.4.10

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

Remote Memory Exposure

  • Vulnerable module: request
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0
    Remediation: Open PR to patch request@2.30.0.

Overview

request is a simplified http request client.

Affected versions of this package are vulnerable to Remote Memory Exposure. A potential remote memory exposure vulnerability exists in request. If a request uses a multipart attachment and the body type option is number with value X, then X bytes of uninitialized memory will be sent in the body of the request.

Note that while the impact of this vulnerability is high (memory exposure), exploiting it is likely difficult, as the attacker needs to somehow control the body type of the request. One potential exploit scenario is when a request is composed based on JSON input, including the body type, allowing a malicious JSON to trigger the memory leak.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with non zero-ed out memory. Example:

var x = new Buffer(100); // uninitialized Buffer of length 100
// vs
var x = new Buffer('100'); // initialized Buffer with value of '100'

Initializing a multipart body in such manner will cause uninitialized memory to be sent in the body of the request.

Proof of concept

var http = require('http')
var request = require('request')

http.createServer(function (req, res) {
  var data = ''
  req.setEncoding('utf8')
  req.on('data', function (chunk) {
    console.log('data')
    data += chunk
  })
  req.on('end', function () {
    // this will print uninitialized memory from the client
    console.log('Client sent:\n', data)
  })
  res.end()
}).listen(8000)

request({
  method: 'POST',
  uri: 'http://localhost:8000',
  multipart: [{ body: 1000 }]
},
function (err, res, body) {
  if (err) return console.error('upload failed:', err)
  console.log('sent')
})

Remediation

Upgrade request to version 2.68.0 or higher.

References

medium severity

Uninitialized Memory Exposure

  • Vulnerable module: tunnel-agent
  • Introduced through: generator-angular@0.16.0 and generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 tunnel-agent@0.3.0
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 caw@1.2.0 tunnel-agent@0.4.3
    Remediation: Open PR to patch tunnel-agent@0.4.3.

Overview

tunnel-agent is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.

A possible memory disclosure vulnerability exists when a value of type number is used to set the proxy.auth option of a request request and results in a possible uninitialized memory exposures in the request body.

This is a result of unobstructed use of the Buffer constructor, whose insecure default constructor increases the odds of memory leakage.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with raw (not "zero-ed") memory.

In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":

// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');

tunnel-agent's request construction uses the default Buffer constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed flaw in OpenSSL.

Proof of concept by ChALkeR

require('request')({
  method: 'GET',
  uri: 'http://www.example.com',
  tunnel: true,
  proxy:{
      protocol: 'http:',
      host:"127.0.0.1",
      port:8080,
      auth:80
  }
});

You can read more about the insecure Buffer behavior on our blog.

Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.

Remediation

Upgrade tunnel-agent to version 0.6.0 or higher. Note This is vulnerable only for Node <=4

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: generator-angular@0.16.0, generator-famous@0.9.2 and others

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 wiredep@2.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 inquirer@0.4.1 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 cheerio@0.17.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 file-utils@0.2.2 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 inquirer@0.7.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 gruntfile-editor@0.2.0 ast-query@0.2.5 lodash@2.4.2
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 file-utils@0.1.5 lodash@2.1.0
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 stacky@1.3.1 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 inquirer@0.11.4 lodash@3.10.1
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 html-wiring@1.2.0 cheerio@0.19.0 lodash@3.10.1

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). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.

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 4.17.11 or higher.

References

medium severity

NULL Pointer Dereference

  • Vulnerable module: node-sass
  • Introduced through: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: node-sass@6.0.1

Detailed paths

  • Introduced through: diamonds@0.0.9-q node-sass@6.0.1

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: yo@4.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q yo@4.3.0 yeoman-doctor@5.0.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

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

Arbitrary Code Injection

  • Vulnerable module: ejs
  • Introduced through: generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 mem-fs-editor@2.3.0 ejs@2.7.4
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 ejs@2.7.4
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 mem-fs-editor@4.0.3 ejs@2.7.4
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 ejs@2.7.4
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 ejs@2.7.4
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 yeoman-test@1.9.1 yeoman-generator@2.0.5 yeoman-environment@2.10.3 yeoman-generator@4.13.0 yeoman-environment@2.10.3 mem-fs-editor@6.0.0 ejs@2.7.4

Overview

ejs is a popular JavaScript templating engine.

Affected versions of this package are vulnerable to Arbitrary Code Injection via the render and renderFile. If external input is flowing into the options parameter, an attacker is able run arbitrary code. This include the filename, compileDebug, and client option.

POC

let ejs = require('ejs')
ejs.render('./views/test.ejs',{
    filename:'/etc/passwd\nfinally { this.global.process.mainModule.require(\'child_process\').execSync(\'touch EJS_HACKED\') }',
    compileDebug: true,
    message: 'test',
    client: true
})

Remediation

Upgrade ejs to version 3.1.6 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: braces
  • Introduced through: web-component-tester@6.9.2 and generator-polymer@1.3.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 http-proxy-middleware@0.17.4 micromatch@2.3.11 braces@1.8.5
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 braces@1.8.5
  • Introduced through: diamonds@0.0.9-q web-component-tester@6.9.2 polyserve@0.27.15 polymer-build@3.1.4 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 braces@1.8.5
  • Introduced through: diamonds@0.0.9-q generator-polymer@1.3.0 yeoman-generator@0.22.6 download@4.4.3 gulp-decompress@1.2.0 decompress@3.0.0 vinyl-fs@2.4.4 glob-stream@5.3.5 micromatch@2.3.11 braces@1.8.5

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: generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 debug@1.0.5

Overview

debug is a JavaScript debugging utility modelled after Node.js core's debugging technique..

debug uses printf-style formatting. Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks via the the %o formatter (Pretty-print an Object all on a single line). It used a regular expression (/\s*\n\s*/g) in order to strip whitespaces and replace newlines with spaces, in order to join the data into a single line. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.

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 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: hawk
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 hawk@1.0.0
    Remediation: Open PR to patch hawk@1.0.0.

Overview

hawk is an HTTP authentication scheme using a message authentication code (MAC) algorithm to provide partial HTTP request cryptographic verification.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks.

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.

You can read more about Regular Expression Denial of Service (ReDoS) on our blog.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: mime
  • Introduced through: generator-angular@0.16.0

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 mime@1.2.11
    Remediation: Open PR to patch mime@1.2.11.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 mime@1.2.11
    Remediation: Open PR to patch mime@1.2.11.
  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 request@2.30.0 form-data@0.1.4 mime@1.2.11
    Remediation: Open PR to patch mime@1.2.11.

Overview

mime is a comprehensive, compact MIME type module.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/ in its lookup, which can cause a slowdown of 2 seconds for 50k characters.

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 mime to version 1.4.1, 2.0.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tar
  • Introduced through: generator-angular@0.16.0 and generator-famous@0.9.2

Detailed paths

  • Introduced through: diamonds@0.0.9-q generator-angular@0.16.0 yeoman-generator@0.16.0 download@0.1.19 decompress@0.2.5 tar@0.1.20
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tar@1.0.3 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-tarbz2@1.0.2 tar@1.0.3
  • Introduced through: diamonds@0.0.9-q generator-famous@0.9.2 yeoman-generator@0.17.7 download@1.0.7 decompress@1.0.7 decompress-targz@1.0.3 tar@1.0.3

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