suitcss-preprocessor@4.0.0

Vulnerabilities

13 via 100 paths

Dependencies

414

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 3
  • 9
  • 1
Status
  • 13
  • 0
  • 0

high severity

Arbitrary Code Execution

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

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 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
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: normalize-url
  • Introduced through: cssnano@3.10.0

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-normalize-url@3.0.8 normalize-url@1.9.1
    Remediation: Upgrade to cssnano@4.0.0.

Overview

normalize-url is a Normalize a URL

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to exponential performance in data URLs.

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 normalize-url to version 6.0.1, 5.3.1, 4.5.1 or higher.

References

high severity
new

Denial of Service (DoS)

  • Vulnerable module: trim-newlines
  • Introduced through: stylelint@7.13.0 and stylelint-config-suitcss@11.0.0

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to stylelint@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 meow@3.7.0 trim-newlines@1.0.0
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 meow@3.7.0 trim-newlines@1.0.0

Overview

trim-newlines is a Trim newlines from the start and/or end of a string

Affected versions of this package are vulnerable to Denial of Service (DoS) via the end() method.

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade trim-newlines to version 3.0.1, 4.0.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: color-string
  • Introduced through: postcss-color-function@3.0.0 and cssnano@3.10.0

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 postcss-color-function@3.0.0 css-color-function@1.3.3 color@0.11.4 color-string@0.3.0
  • Introduced through: suitcss-preprocessor@4.0.0 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: doiuse
  • Introduced through: stylelint@7.13.0 and stylelint-config-suitcss@11.0.0

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 doiuse@2.6.0
    Remediation: Upgrade to stylelint@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 doiuse@2.6.0
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 doiuse@2.6.0

Overview

doiuse is a Lint CSS for browser support against caniuse database

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

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 doiuse to version 4.4.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: chokidar@1.7.0, stylelint@7.13.0 and others

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 chokidar@1.7.0 glob-parent@2.0.0
    Remediation: Upgrade to chokidar@3.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: suitcss-preprocessor@4.0.0 chokidar@1.7.0 anymatch@1.3.2 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0

Overview

glob-parent is a package that helps extracting the non-magic parent path from a glob string.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure regex used to check for strings ending in enclosure containing path separator.

PoC by Yeting Li

var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}

return ret;
}

globParent(build_attack(5000));

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 glob-parent to version 5.1.2 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: suitcss-preprocessor@4.0.0 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: suitcss-preprocessor@4.0.0 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: suitcss-preprocessor@4.0.0 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: postcss@5.2.18, autoprefixer@6.7.7 and others

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 postcss@5.2.18
    Remediation: Upgrade to postcss@8.2.13.
  • Introduced through: suitcss-preprocessor@4.0.0 autoprefixer@6.7.7 postcss@5.2.18
    Remediation: Upgrade to autoprefixer@10.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-calc@5.3.1 postcss@5.2.18
    Remediation: Upgrade to postcss-calc@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@5.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-apply@0.6.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-autoreset@1.2.1 postcss@5.2.18
    Remediation: Upgrade to postcss-autoreset@3.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-bem-linter@2.7.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-color-function@3.0.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-custom-media@5.0.1 postcss@5.2.18
    Remediation: Upgrade to postcss-custom-media@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-custom-properties@5.0.2 postcss@5.2.18
    Remediation: Upgrade to postcss-custom-properties@11.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-easy-import@2.1.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-reporter@3.0.0 postcss@5.2.18
    Remediation: Upgrade to postcss-reporter@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 autoprefixer@6.7.7 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 autoprefixer@6.7.7 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-calc@5.3.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-colormin@2.2.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-convert-values@2.6.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-discard-comments@2.0.4 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-discard-duplicates@2.1.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-discard-empty@2.1.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-discard-overridden@0.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-discard-unused@2.2.3 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-filter-plugins@2.0.3 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-merge-idents@2.1.7 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-merge-longhand@2.0.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-merge-rules@2.1.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-minify-font-values@1.0.5 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-minify-gradients@1.0.5 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-minify-params@1.2.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-minify-selectors@2.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-normalize-charset@1.1.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-normalize-url@3.0.8 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-ordered-values@2.2.3 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-reduce-idents@2.4.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-reduce-initial@1.0.1 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-reduce-transforms@1.0.4 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-svgo@2.1.6 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-unique-selectors@2.0.2 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 cssnano@3.10.0 postcss-zindex@2.2.0 postcss@5.2.18
    Remediation: Upgrade to cssnano@4.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-autoreset@1.2.1 postcss-js@0.1.3 postcss@5.2.18
    Remediation: Upgrade to postcss-autoreset@3.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 postcss-easy-import@2.1.0 postcss-import@9.1.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 postcss-reporter@3.0.0 postcss@5.2.18
    Remediation: Upgrade to stylelint@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 colorguard@1.2.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 doiuse@2.6.0 postcss@5.2.18
    Remediation: Upgrade to stylelint@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 postcss-less@0.14.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 postcss-scss@0.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 stylehacks@2.3.2 postcss@5.2.18
    Remediation: Upgrade to stylelint@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 sugarss@0.2.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 colorguard@1.2.1 postcss-reporter@1.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 stylehacks@2.3.2 postcss-reporter@1.4.1 postcss@5.2.18
    Remediation: Upgrade to stylelint@8.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 autoprefixer@6.7.7 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 autoprefixer@6.7.7 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 postcss-reporter@3.0.0 postcss@5.2.18
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 postcss-reporter@3.0.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 colorguard@1.2.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 colorguard@1.2.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 doiuse@2.6.0 postcss@5.2.18
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 doiuse@2.6.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 postcss-less@0.14.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 postcss-less@0.14.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 postcss-scss@0.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 postcss-scss@0.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 stylehacks@2.3.2 postcss@5.2.18
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 stylehacks@2.3.2 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 sugarss@0.2.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 sugarss@0.2.0 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 colorguard@1.2.1 postcss-reporter@1.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 colorguard@1.2.1 postcss-reporter@1.4.1 postcss@5.2.18
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 stylehacks@2.3.2 postcss-reporter@1.4.1 postcss@5.2.18
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 stylehacks@2.3.2 postcss-reporter@1.4.1 postcss@5.2.18

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 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: stylelint
  • Introduced through: stylelint@7.13.0 and stylelint-config-suitcss@11.0.0

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0
    Remediation: Upgrade to stylelint@11.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0

Overview

stylelint is a linter that helps you avoid errors and enforce conventions in your styles.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade stylelint to version 11.0.0 or higher.

References

medium severity

Arbitrary Code Injection

  • Vulnerable module: underscore
  • Introduced through: object-assign-deep@0.0.4

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 object-assign-deep@0.0.4 underscore@1.7.0
    Remediation: Upgrade to object-assign-deep@0.1.0.

Overview

underscore is a JavaScript's functional programming helper library.

Affected versions of this package are vulnerable to Arbitrary Code Injection via the template function, particularly when the variable option is taken from _.templateSettings as it is not sanitized.

PoC

const _ = require('underscore');
_.templateSettings.variable = "a = this.process.mainModule.require('child_process').execSync('touch HELLO')";
const t = _.template("")();

Remediation

Upgrade underscore to version 1.13.0-2, 1.12.1 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: braces
  • Introduced through: stylelint@7.13.0, chokidar@1.7.0 and others

Detailed paths

  • Introduced through: suitcss-preprocessor@4.0.0 stylelint@7.13.0 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to stylelint@9.8.0.
  • Introduced through: suitcss-preprocessor@4.0.0 chokidar@1.7.0 anymatch@1.3.2 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to chokidar@2.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-order@0.4.4 stylelint@7.13.0 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to stylelint-config-suitcss@13.0.0.
  • Introduced through: suitcss-preprocessor@4.0.0 stylelint-config-suitcss@11.0.0 stylelint-suitcss@1.0.0 stylelint@7.13.0 micromatch@2.3.11 braces@1.8.5
    Remediation: Upgrade to stylelint-config-suitcss@14.0.0.

Overview

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

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.

Disclosure Timeline

  • Feb 15th, 2018 - Initial Disclosure to package owner
  • Feb 16th, 2018 - Initial Response from package owner
  • Feb 18th, 2018 - Fix issued
  • Feb 19th, 2018 - Vulnerability published

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 braces to version 2.3.1 or higher.

References