@affectionatedoor/gatsby-theme-ui@3.2.0

Vulnerabilities

8 via 32 paths

Dependencies

939

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 5
  • 3
Status
  • 8
  • 0
  • 0

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: gatsby-plugin-sharp@2.14.4 and gatsby-plugin-mdx@1.10.1

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-sharp@2.14.4 svgo@1.3.2 css-select@2.1.0 nth-check@1.0.2
  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-mdx@1.10.1 static-site-generator-webpack-plugin@3.4.2 cheerio@0.22.0 css-select@1.2.0 nth-check@1.0.2

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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @mdx-js/mdx@1.6.22 and gatsby-plugin-mdx@1.10.1

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 @mdx-js/mdx@1.6.22 remark-parse@8.0.3 trim@0.0.1
  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 @mdx-js/mdx@1.6.22 remark-mdx@1.6.22 remark-parse@8.0.3 trim@0.0.1
  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-mdx@1.10.1 remark@10.0.1 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-plugin-mdx@1.10.1

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-mdx@1.10.1 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

Arbitrary File Write via Archive Extraction (Zip Slip)

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

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: css-what
  • Introduced through: gatsby-plugin-mdx@1.10.1 and gatsby-plugin-sharp@2.14.4

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-mdx@1.10.1 static-site-generator-webpack-plugin@3.4.2 cheerio@0.22.0 css-select@1.2.0 css-what@2.1.3
  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 gatsby-plugin-sharp@2.14.4 svgo@1.3.2 css-select@2.1.0 css-what@3.4.2

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

Detailed paths

  • Introduced through: @affectionatedoor/gatsby-theme-ui@3.2.0 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: @affectionatedoor/gatsby-theme-ui@3.2.0 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