Snyk test report

Infinite loop

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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

• GitHub Issue
• Vulnerable Code
• Vulnerable Code

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Heap-based Buffer Overflow

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Overview

sharp is a High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP, GIF, AVIF and TIFF images

Affected versions of this package are vulnerable to Heap-based Buffer Overflow in the VipsForeignLoadHeif process. An attacker can execute arbitrary code by providing specially crafted AVIF images as input.

Workaround

This vulnerability can be mitigated by blocking the decoding of AVIF images using the configuration sharp.block({ operation: ["VipsForeignLoadHeif"] }); and by ensuring the Node.js executable is compiled as a Position Independent Executable (PIE).

Remediation

Upgrade sharp to version 0.35.4 or higher.

References

• GitHub Release
• Maintainer's Advisory

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Use After Free

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Overview

sharp is a High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP, GIF, AVIF and TIFF images

Affected versions of this package are vulnerable to Use After Free in entity_insert() and the entity map held on XmlState, which is shared between the outer parse and a recursive XInclude, so inserting an entity whose name already exists replaces the first entry and its Drop implementation calls xmlFreeNode() while the outer xmlCtxtParseEntity() is still using that 144 byte xmlEntity. An attacker can corrupt process memory by supplying an SVG document whose xi:include pulls in another document redefining an entity that is already active. This requires the application to parse attacker supplied SVG with XInclude processing reached, and the entity names must collide across the outer document and the included one.

Remediation

Upgrade sharp to version 0.35.5 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitLab Work Item
• Red Hat Bugzilla Bug
• RustSec Advisory
• PoC in GitHub

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Uncaught Exception

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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 via stringify when arrayFormat: 'comma' is used with array elements that have a non-callable toString property. Such elements - as produced by JSON.parse, or by qs.parse under allowPrototypes or plainObjects (which yields null-prototype objects) - cause Array.prototype.join or utils.encode to throw a TypeError: Cannot convert object to primitive value, crashing the process.

Note: This is only exploitable if the arrayFormat: 'comma' option is explicitly set.

Remediation

Upgrade qs to version 6.16.1 or higher.

References

• GitHub Advisory
• GitHub Commit

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Regular Expression Denial of Service (ReDoS)

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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.

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 picomatch.

References

• GitHub PR
• Vulnerable Code

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