handroll@0.17.13

Vulnerabilities

9 via 94 paths

Dependencies

334

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 3
  • 6
Status
  • 9
  • 0
  • 0

high severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@5.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@5.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 autoprefixer@6.7.7 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-calc@5.3.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-colormin@2.2.2 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-convert-values@2.6.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-comments@2.0.4 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-duplicates@2.1.0 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-empty@2.1.0 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-overridden@0.1.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-unused@2.2.3 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-filter-plugins@2.0.3 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-idents@2.1.7 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-longhand@2.0.2 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-rules@2.1.2 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-font-values@1.0.5 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-gradients@1.0.5 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-params@1.2.2 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-selectors@2.1.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-charset@1.1.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-url@3.0.8 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-ordered-values@2.2.3 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-idents@2.4.0 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-initial@1.0.1 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-transforms@1.0.4 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-unique-selectors@2.0.2 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-zindex@2.2.0 postcss@5.2.18 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 autoprefixer@6.7.7 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-calc@5.3.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-colormin@2.2.2 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-convert-values@2.6.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-comments@2.0.4 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-duplicates@2.1.0 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-empty@2.1.0 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-overridden@0.1.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-unused@2.2.3 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-filter-plugins@2.0.3 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-idents@2.1.7 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-longhand@2.0.2 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-rules@2.1.2 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-font-values@1.0.5 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-gradients@1.0.5 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-params@1.2.2 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-selectors@2.1.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-charset@1.1.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-url@3.0.8 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-ordered-values@2.2.3 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-idents@2.4.0 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-initial@1.0.1 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-transforms@1.0.4 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-unique-selectors@2.0.2 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-zindex@2.2.0 postcss@5.2.18 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 svgo@0.7.2 csso@2.3.2 clap@1.2.3 chalk@1.1.3 has-ansi@2.0.0 ansi-regex@2.1.1
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 svgo@0.7.2 csso@2.3.2 clap@1.2.3 chalk@1.1.3 strip-ansi@3.0.1 ansi-regex@2.1.1

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]* and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*.

PoC

import ansiRegex from 'ansi-regex';

for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = "\u001B["+";".repeat(i*10000);
    ansiRegex().test(attack_str)
    var time_cost = Date.now() - time;
    console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

  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 ansi-regex to version 6.0.1, 5.0.1 or higher.

References

high severity

Arbitrary Code Execution

  • Vulnerable module: js-yaml
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 svgo@0.7.2 js-yaml@3.7.0
    Remediation: Upgrade to cssnano@4.0.0.

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: rollup-plugin-pug@0.1.6

Detailed paths

  • Introduced through: handroll@0.17.13 rollup-plugin-pug@0.1.6 pug@2.0.4

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

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: color-string
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-colormin@2.2.2 colormin@1.1.2 color@0.11.4 color-string@0.3.0

Overview

color-string is a Parser and generator for CSS color strings

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the hwb regular expression in the cs.get.hwb function in index.js. The affected regular expression exhibits quadratic worst-case time complexity.

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 color-string to version 1.5.5 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: is-svg
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 is-svg@2.1.0
    Remediation: Upgrade to cssnano@4.0.0.

Overview

is-svg is a Check if a string or buffer is SVG

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If an attacker provides a malicious string, is-svg will get stuck processing the input for a very long time.

You are only affected if you use this package on a server that accepts SVG as 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 is-svg to version 4.2.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: is-svg
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 is-svg@2.1.0
    Remediation: Upgrade to cssnano@4.0.0.

Overview

is-svg is a Check if a string or buffer is SVG

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the removeDtdMarkupDeclarations and entityRegex regular expressions, bypassing the fix for CVE-2021-28092.

PoC by Yeting Li

//1) 1st ReDoS caused by the two sub-regexes [A-Z]+ and [^>]* in `removeDtdMarkupDeclarations`.
const isSvg = require('is-svg');
function build_attack1(n) {
var ret = '<!'
for (var i = 0; i < n; i++) {
ret += 'DOCTYPE'
}

return ret+"";
}
for(var i = 1; i <= 50000; i++) {
   if (i % 10000 == 0) {
       var time = Date.now();
       var attack_str = build_attack1(i);
       isSvg(attack_str);

       var time_cost = Date.now() - time;
       console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
 }
}

//2) 2nd ReDoS caused by ? the first sub-regex  \s*  in `entityRegex`.
function build_attack2(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_attack2(i);
       isSvg(attack_str);

       var time_cost = Date.now() - time;
       console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
 }
}


//3rd ReDoS caused by the sub-regex \s+\S*\s*  in `entityRegex`.
function build_attack3(n) {
var ret = '<!Entity'
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_attack3(i);
       isSvg(attack_str);

       var time_cost = Date.now() - time;
       console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
 }
}

//4th ReDoS caused by the sub-regex \S*\s*(?:"|')[^"]+  in `entityRegex`.
function build_attack4(n) {
var ret = '<!Entity '
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_attack4(i);
       isSvg(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 is-svg to version 4.3.0 or higher.

References

medium severity

Denial of Service (DoS)

  • Vulnerable module: js-yaml
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 svgo@0.7.2 js-yaml@3.7.0
    Remediation: Upgrade to cssnano@4.0.0.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). The parsing of a specially crafted YAML file may exhaust the system resources.

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 js-yaml to version 3.13.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: postcss
  • Introduced through: lost@8.3.1 and poststylus@1.0.1

Detailed paths

  • Introduced through: handroll@0.17.13 lost@8.3.1 postcss@7.0.14
  • Introduced through: handroll@0.17.13 poststylus@1.0.1 postcss@8.0.9

Overview

postcss is a PostCSS is a tool for transforming styles with JS plugins.

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

PoC

var postcss = require("postcss")
function build_attack(n) {
    var ret = "a{}/*# sourceMappingURL="
    for (var i = 0; i < n; i++) {
        ret += " "
    }
    return ret + "!";
}

// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            postcss.parse(attack_str)
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        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 postcss to version 7.0.36, 8.2.10 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: postcss
  • Introduced through: autoprefixer@8.6.5, cssnano@3.10.0 and others

Detailed paths

  • Introduced through: handroll@0.17.13 autoprefixer@8.6.5 postcss@6.0.23
    Remediation: Upgrade to autoprefixer@9.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.1.1.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 autoprefixer@6.7.7 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-calc@5.3.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-colormin@2.2.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-convert-values@2.6.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-comments@2.0.4 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-duplicates@2.1.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-empty@2.1.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-overridden@0.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-discard-unused@2.2.3 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-filter-plugins@2.0.3 postcss@5.2.18
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-idents@2.1.7 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-longhand@2.0.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-merge-rules@2.1.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-font-values@1.0.5 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-gradients@1.0.5 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-params@1.2.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-minify-selectors@2.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-charset@1.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-normalize-url@3.0.8 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-ordered-values@2.2.3 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-idents@2.4.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-initial@1.0.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-reduce-transforms@1.0.4 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-svgo@2.1.6 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-unique-selectors@2.0.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 cssnano@3.10.0 postcss-zindex@2.2.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: handroll@0.17.13 lost@8.3.1 postcss@7.0.14
  • Introduced through: handroll@0.17.13 poststylus@1.0.1 postcss@8.0.9

Overview

postcss is a PostCSS is a tool for transforming styles with JS plugins.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via getAnnotationURL() and loadAnnotation() in lib/previous-map.js. The vulnerable regexes are caused mainly by the sub-pattern \/\*\s*# sourceMappingURL=(.*).

PoC

var postcss = require("postcss")
function build_attack(n) {
    var ret = "a{}"
    for (var i = 0; i < n; i++) {
        ret += "/*# sourceMappingURL="
    }
    return ret + "!";
}

// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            postcss.parse(attack_str)
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        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 postcss to version 8.2.13, 7.0.36 or higher.

References