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Overview

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

Affected versions of this package are vulnerable to Uncontrolled Recursion in the recursive AST walkers, which lack depth guards. An attacker can supply deeply nested brace patterns that stay within the character limit to exhaust the call stack and crash the Node.js process with an uncaught RangeError.

Remediation

There is no fixed version for braces.

References

• GitHub Issue
• Vulnerable Code
• Vulnerable Code
• Vulnerable Code

Overview

Affected versions of this package are vulnerable to Uncontrolled Recursion via the parse function due to using a recursive revive() phase to resolve circular references in deserialized JSON. An attacker can cause a stack overflow and crash the process by supplying a crafted payload with deeply nested or self-referential indices.

PoC

const flatted = require('flatted');

// Build deeply nested circular reference chain
const depth = 20000;
const arr = new Array(depth + 1);
arr[0] = '{"a":"1"}';
for (let i = 1; i <= depth; i++) {
  arr[i] = `{"a":"${i + 1}"}`;
}
arr[depth] = '{"a":"leaf"}';

const payload = JSON.stringify(arr);
flatted.parse(payload); // RangeError: Maximum call stack size exceeded

Remediation

Upgrade flatted to version 3.4.0 or higher.

References

• GitHub Commit
• GitHub PR

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

• GitHub Advisory
• GitHub Commit
• GitHub Release

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.

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

• GitHub Advisory
• GitHub Commit
• Red Hat Bugzilla Bug

Overview

markdown-it is a modern pluggable markdown parser.

Affected versions of this package are vulnerable to Unchecked Input for Loop Condition via the process_inlines function in src/rules_core/smartquotes.ts when the typographer option is enabled. The smartquotes rule performs a linear scan of the opener stack for every closing quote token, resulting in quadratic time complexity when quote types do not match. An attacker can supply input with a large number of unmatched quote characters to cause a crash through excessive CPU consumption.

Note: This is only exploitable when the typographer: true option is explicitly set, as the default configuration (typographer: false) does not invoke the smartquotes rule.

Remediation

Upgrade markdown-it to version 15.0.2, 14.3.2 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Commit
• GitHub Commit
• GitHub Release
• GitHub Release
• Red Hat Bugzilla Bug

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via analyzeRepeatedExtglob in lib/parse.js, which skips single-branch repeated extglob patterns such as +(*) or +(*a). An attacker can supply these glob patterns to trigger exponential backtracking in the underlying regular expression engine against short inputs, blocking the Node.js event loop and crashing the application.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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 picomatch.

References

• GitHub PR
• Vulnerable Code

Overview

hexo is an A fast, simple & powerful blog framework, powered by Node.js.

Affected versions of this package are vulnerable to Directory Traversal via the Hexo's file read functionality. An attacker can read arbitrary files by manipulating the file path input.

Note:

This issue is only exploitable if the attacker has the ability to control the file path input. This vulnerability was only verified successfully in the Windows environment.

PoC

{% include_code ..\..\..\..\..\..\..\..\..\..\..\test.txt %}

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 hexo to version 7.2.0 or higher.

References

• GitHub Commit
• GitHub Issue
• GitHub PR
• Vulnerable Code

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

• GitHub Diff
• GitHub Issue