gatsby-theme-ghost-casper@0.0.1

Vulnerabilities

18 via 68 paths

Dependencies

1935

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 1
  • 8
  • 9
Status
  • 18
  • 0
  • 0

critical severity

Arbitrary Code Execution

  • Vulnerable module: sanitize-html
  • Introduced through: gatsby-transformer-remark@2.16.1

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 sanitize-html@1.27.5

Overview

sanitize-html is a library that allows you to clean up user-submitted HTML, preserving whitelisted elements and whitelisted attributes on a per-element basis

Affected versions of this package are vulnerable to Arbitrary Code Execution. Tag transformations which turn an attribute value into a text node using transformTags could be vulnerable to code execution.

Remediation

Upgrade sanitize-html to version 2.0.0-beta or higher.

References

high severity
new

Remote Code Execution (RCE)

  • Vulnerable module: shell-quote
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 react-dev-utils@4.2.3 shell-quote@1.6.1

Overview

shell-quote is a package used to quote and parse shell commands.

Affected versions of this package are vulnerable to Remote Code Execution (RCE). An attacker can inject unescaped shell metacharacters through a regex designed to support Windows drive letters. If the output of this package is passed to a real shell as a quoted argument to a command with exec(), an attacker can inject arbitrary commands. This is because the Windows drive letter regex character class is {A-z] instead of the correct {A-Za-z]. Several shell metacharacters exist in the space between capital letter Z and lower case letter a, such as the backtick character.

Remediation

Upgrade shell-quote to version 1.7.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-html
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 ansi-html@0.0.7
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 @pmmmwh/react-refresh-webpack-plugin@0.4.3 ansi-html@0.0.7
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 ansi-html@0.0.7

Overview

ansi-html is an An elegant lib that converts the chalked (ANSI) text to HTML.

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

PoC

require('ansi-html')('x1b[0mx1b[' + '0'.repeat(35))

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

There is no fixed version for ansi-html.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 @pieh/friendly-errors-webpack-plugin@1.7.0-chalk-2 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 react-dev-utils@4.2.3 inquirer@3.3.0 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 react-dev-utils@4.2.3 inquirer@3.3.0 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 eslint@6.8.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 gatsby-cli@2.19.3 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 gatsby-cli@2.19.3 yurnalist@2.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 eslint@6.8.0 table@5.4.6 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 yargs@13.3.2 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.13.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 yargs@13.3.2 cliui@5.0.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.13.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 yargs@13.3.2 cliui@5.0.0 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.13.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 yargs@13.3.2 cliui@5.0.0 wrap-ansi@5.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.13.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 yargs@13.3.2 cliui@5.0.0 wrap-ansi@5.1.0 string-width@3.1.0 strip-ansi@5.2.0 ansi-regex@4.1.0
    Remediation: Upgrade to gatsby@3.13.0.

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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: gatsby-remark-images@2.0.6, gatsby-transformer-remark@2.16.1 and others

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-remark-images@2.0.6 unist-util-select@1.5.0 nth-check@1.0.2
    Remediation: Upgrade to gatsby-remark-images@5.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 unist-util-select@1.5.0 nth-check@1.0.2
    Remediation: Upgrade to gatsby-transformer-remark@4.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-yaml@2.11.0 unist-util-select@1.5.0 nth-check@1.0.2
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 svgo@1.3.2 css-select@2.1.0 nth-check@1.0.2
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 cssnano@4.1.11 cssnano-preset-default@4.0.8 postcss-svgo@4.0.3 svgo@1.3.2 css-select@2.1.0 nth-check@1.0.2
    Remediation: Upgrade to gatsby-theme-ghost-casper@0.0.2.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 optimize-css-assets-webpack-plugin@5.0.8 cssnano@4.1.11 cssnano-preset-default@4.0.8 postcss-svgo@4.0.3 svgo@1.3.2 css-select@2.1.0 nth-check@1.0.2
    Remediation: Upgrade to gatsby@3.0.0.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) mainly due to the sub-pattern \s*(?:([+-]?)\s*(\d+))? in RE_NTH_ELEMENT with quantified overlapping adjacency.

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 nth-check to version 2.0.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: gatsby-plugin-sharp@2.14.4

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). This can occur when running the regex on untrusted user input in a server context.

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 semver-regex to version 4.0.1, 3.1.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: gatsby-plugin-sharp@2.14.4

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

Overview

semver-regex is a Regular expression for matching semver versions

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). semverRegex function contains a regex that allows exponential backtracking.

PoC

import semverRegex from 'semver-regex';

// The following payload would take excessive CPU cycles
var payload = '0.0.0-0' + '.-------'.repeat(100000) + '@';
semverRegex().test(payload);

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 semver-regex to version 3.1.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: trim
  • Introduced through: gatsby-transformer-remark@2.16.1 and gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 remark-parse@6.0.3 trim@0.0.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 mdast-util-to-hast@3.0.4 trim@0.0.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 remark@10.0.1 remark-parse@6.0.3 trim@0.0.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 gatsby-cli@2.19.3 gatsby-recipes@0.9.3 remark-parse@6.0.3 trim@0.0.1

Overview

trim is a Trim string whitespace

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

PoC by Liyuan Chen:


function build_attack (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}

return ret + "1";
}
var time = Date.now();
trim(build_attack(50000))
var time_cost = Date.now() - time;
console.log("time_cost: " + time_cost)```

## 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:
```js
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 trim to version 0.0.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: underscore.string
  • Introduced through: gatsby-transformer-remark@2.16.1

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 underscore.string@3.3.5

Overview

underscore.string is a Javascript lacks complete string manipulation operations.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

There is no fixed version for underscore.string.

References

medium severity

Access Restriction Bypass

  • Vulnerable module: sanitize-html
  • Introduced through: gatsby-transformer-remark@2.16.1

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 sanitize-html@1.27.5

Overview

sanitize-html is a library that allows you to clean up user-submitted HTML, preserving whitelisted elements and whitelisted attributes on a per-element basis

Affected versions of this package are vulnerable to Access Restriction Bypass. Internationalized domain name (IDN) is not properly handled. This allows attackers to bypass hostname whitelist validation set by the allowedIframeHostnames option.

Remediation

Upgrade sanitize-html to version 2.3.1 or higher.

References

medium severity

Validation Bypass

  • Vulnerable module: sanitize-html
  • Introduced through: gatsby-transformer-remark@2.16.1

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-transformer-remark@2.16.1 sanitize-html@1.27.5

Overview

sanitize-html is a library that allows you to clean up user-submitted HTML, preserving whitelisted elements and whitelisted attributes on a per-element basis

Affected versions of this package are vulnerable to Validation Bypass. There is no proper validation of the hostnames set by the allowedIframeHostnames option when the allowIframeRelativeUrls is set to true. This allows attackers to bypass the hostname whitelist for the iframe element.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

Upgrade sanitize-html to version 2.3.2 or higher.

References

medium severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress-tar
  • Introduced through: gatsby-plugin-sharp@2.14.4

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-tarbz2@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-build@3.0.0 download@6.2.5 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 download@7.1.0 decompress@4.2.1 decompress-targz@4.1.1 decompress-tar@4.1.1

Overview

decompress-tar is a tar plugin for decompress.

Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip). It is possible to bypass the security measures provided by decompress and conduct ZIP path traversal through symlinks.

PoC

const decompress = require('decompress');

decompress('slip.tar.gz', 'dist').then(files => {
    console.log('done!');
});

Details

It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:


+2018-04-15 22:04:29 ..... 19 19 good.txt

+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys

Remediation

There is no fixed version for decompress-tar.

References

medium severity

Command Injection

  • Vulnerable module: react-dev-utils
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 react-dev-utils@4.2.3
    Remediation: Upgrade to gatsby@3.0.0.

Overview

react-dev-utils is an includes some utilities used by Create React App.

Affected versions of this package are vulnerable to Command Injection via getProcessForPort - where an input argument is concatenated into a command string to be executed. This function is typically used from react-scripts (in Create React App projects), where the usage is safe. Only when this function is manually invoked with user-provided values (ie: by custom code) is there the potential for command injection. If you're consuming it from react-scripts then this issue does not affect you.

Remediation

Upgrade react-dev-utils to version 11.0.4 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: css-what
  • Introduced through: gatsby-plugin-sharp@2.14.4, cssnano@4.1.11 and others

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 svgo@1.3.2 css-select@2.1.0 css-what@3.4.2
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 cssnano@4.1.11 cssnano-preset-default@4.0.8 postcss-svgo@4.0.3 svgo@1.3.2 css-select@2.1.0 css-what@3.4.2
    Remediation: Upgrade to gatsby-theme-ghost-casper@0.0.2.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 optimize-css-assets-webpack-plugin@5.0.8 cssnano@4.1.11 cssnano-preset-default@4.0.8 postcss-svgo@4.0.3 svgo@1.3.2 css-select@2.1.0 css-what@3.4.2
    Remediation: Upgrade to gatsby@3.0.0.

Overview

css-what is an a CSS selector parser

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

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 css-what to version 5.0.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack-dev-server@3.11.2 chokidar@2.1.8 glob-parent@3.1.0
    Remediation: Upgrade to gatsby@3.13.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 webpack@4.46.0 watchpack@1.7.5 watchpack-chokidar2@2.0.1 chokidar@2.1.8 glob-parent@3.1.0

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: postcss
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 icss-utils@2.1.0 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 postcss-modules-extract-imports@1.2.1 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 postcss-modules-local-by-default@1.2.0 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 postcss-modules-scope@1.1.0 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 css-loader@1.0.1 postcss-modules-values@1.3.0 postcss@6.0.23
    Remediation: Upgrade to gatsby@3.0.0.

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

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ws
  • Introduced through: gatsby@2.32.13

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby@2.32.13 eslint-plugin-graphql@4.0.0 graphql-config@3.4.1 @graphql-tools/url-loader@6.10.1 ws@7.4.5

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A specially crafted value of the Sec-Websocket-Protocol header can be used to significantly slow down a ws server.

##PoC

for (const length of [1000, 2000, 4000, 8000, 16000, 32000]) {
  const value = 'b' + ' '.repeat(length) + 'x';
  const start = process.hrtime.bigint();

  value.trim().split(/ *, */);

  const end = process.hrtime.bigint();

  console.log('length = %d, time = %f ns', length, end - start);
}

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 ws to version 7.4.6, 6.2.2, 5.2.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver-regex
  • Introduced through: gatsby-plugin-sharp@2.14.4

Detailed paths

  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-mozjpeg@9.0.0 mozjpeg@7.1.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0
  • Introduced through: gatsby-theme-ghost-casper@0.0.1 gatsby-plugin-sharp@2.14.4 imagemin-pngquant@9.0.2 pngquant-bin@6.0.1 bin-wrapper@4.1.0 bin-version-check@4.0.0 bin-version@3.1.0 find-versions@3.2.0 semver-regex@2.0.0

Overview

semver-regex is a Regular expression for matching semver versions

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

PoC


// import of the vulnerable library
const semverRegex = require('semver-regex');
// import of measurement tools
const { PerformanceObserver, performance } = require('perf_hooks');

// config of measurements tools
const obs = new PerformanceObserver((items) => {
 console.log(items.getEntries()[0].duration);
 performance.clearMarks();
});
obs.observe({ entryTypes: ['measure'] });

// base version string
let version = "v1.1.3-0a"

// Adding the evil code, resulting in string
// v1.1.3-0aa.aa.aa.aa.aa.aa.a…a.a"
for(let i=0; i < 20; i++) {
   version += "a.a"
}

// produce a good version
// Parses well for the regex in milliseconds
let goodVersion = version + "2"

// good version proof
performance.mark("good before")
const goodresult = semverRegex().test(goodVersion);
performance.mark("good after")


console.log(`Good result: ${goodresult}`)
performance.measure('Good', 'good before', 'good after');

// create a bad/exploit version that is invalid due to the last $ sign
// will cause the nodejs engine to hang, if not, increase the a.a
// additions above a bit.
badVersion = version + "aaaaaaa$"

// exploit proof
performance.mark("bad before")
const badresult = semverRegex().test(badVersion);
performance.mark("bad after")

console.log(`Bad result: ${badresult}`)
performance.measure('Bad', 'bad before', 'bad after');

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 semver-regex to version 3.1.2 or higher.

References