@unchainedshop/gatsby-theme-apollo-docs@4.3.16

Vulnerabilities

13 via 48 paths

Dependencies

975

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 1
  • 4
  • 8
Status
  • 13
  • 0
  • 0

critical severity

Arbitrary Code Execution

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

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 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

Remote Memory Exposure

  • Vulnerable module: bl
  • Introduced through: gatsby-plugin-printer@1.1.1

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-plugin-printer@1.1.1 rollup-plugin-node-builtins@2.1.2 browserify-fs@1.0.0 levelup@0.18.6 bl@0.8.2

Overview

bl is a library that allows you to collect buffers and access with a standard readable buffer interface.

Affected versions of this package are vulnerable to Remote Memory Exposure. If user input ends up in consume() argument and can become negative, BufferList state can be corrupted, tricking it into exposing uninitialized memory via regular .slice() calls.

PoC by chalker

const { BufferList } = require('bl')
const secret = require('crypto').randomBytes(256)
for (let i = 0; i < 1e6; i++) {
  const clone = Buffer.from(secret)
  const bl = new BufferList()
  bl.append(Buffer.from('a'))
  bl.consume(-1024)
  const buf = bl.slice(1)
  if (buf.indexOf(clone) !== -1) {
    console.error(`Match (at ${i})`, buf)
  }
}

Remediation

Upgrade bl to version 2.2.1, 3.0.1, 4.0.3, 1.2.3 or higher.

References

high severity

Command Injection

  • Vulnerable module: lodash.template
  • Introduced through: gatsby-remark-mermaid@1.2.0

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 @percy/migrate@0.10.0 @oclif/plugin-help@3.2.2 lodash.template@4.5.0
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 @percy/migrate@0.10.0 @oclif/command@1.8.0 @oclif/plugin-help@3.2.2 lodash.template@4.5.0
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 @percy/migrate@0.10.0 @oclif/plugin-help@3.2.2 @oclif/command@1.8.0 @oclif/plugin-help@3.2.2 lodash.template@4.5.0

Overview

lodash.template is a The Lodash method _.template exported as a Node.js module.

Affected versions of this package are vulnerable to Command Injection via template.

PoC

var _ = require('lodash');

_.template('', { variable: '){console.log(process.env)}; with(obj' })()

Remediation

There is no fixed version for lodash.template.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: trim
  • Introduced through: @mdx-js/mdx@1.6.22, remark@10.0.1 and others

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 @mdx-js/mdx@1.6.22 remark-parse@8.0.3 trim@0.0.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 remark@10.0.1 remark-parse@6.0.3 trim@0.0.1
    Remediation: Upgrade to remark@13.0.0.
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-transformer-remark@2.16.1 remark-parse@6.0.3 trim@0.0.1
    Remediation: Upgrade to gatsby-transformer-remark@4.0.0.
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-transformer-remark@2.16.1 mdast-util-to-hast@3.0.4 trim@0.0.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 remark-react@5.0.1 mdast-util-to-hast@4.0.0 trim@0.0.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 @mdx-js/mdx@1.6.22 remark-mdx@1.6.22 remark-parse@8.0.3 trim@0.0.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-plugin-mdx@1.10.1 remark@10.0.1 remark-parse@6.0.3 trim@0.0.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-transformer-remark@2.16.1 remark@10.0.1 remark-parse@6.0.3 trim@0.0.1
    Remediation: Upgrade to gatsby-transformer-remark@4.0.0.

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 and gatsby-transformer-remark@2.16.1

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-plugin-mdx@1.10.1 underscore.string@3.3.5
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 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

Uninitialized Memory Exposure

  • Vulnerable module: bl
  • Introduced through: gatsby-plugin-printer@1.1.1

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-plugin-printer@1.1.1 rollup-plugin-node-builtins@2.1.2 browserify-fs@1.0.0 levelup@0.18.6 bl@0.8.2

Overview

bl is a storage object for collections of Node Buffers.

A possible memory disclosure vulnerability exists when a value of type number is provided to the append() method and results in concatenation of uninitialized memory to the buffer collection.

This is a result of unobstructed use of the Buffer constructor, whose insecure default constructor increases the odds of memory leakage.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with raw (not "zero-ed") memory.

In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":

// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');

bl's append function uses the default Buffer constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed flaw in OpenSSL.

const BufferList = require('bl')

var bl = new BufferList()
bl.append(new Buffer('abcd'))
bl.append(new Buffer('efg'))
bl.append('100')
// appends a Buffer holding 100 bytes of uninitialized memory
bl.append(100)                     
bl.append(new Buffer('j'))

You can read more about the insecure Buffer behavior on our blog.

Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.

Note This is vulnerable only for Node <=4

References

medium severity

Regular Expression Denial of Service (ReDoS)

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

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 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

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
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: d3-color
  • Introduced through: gatsby-remark-mermaid@1.2.0

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-scale-chromatic@1.5.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-brush@1.1.6 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-scale@2.2.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-scale-chromatic@1.5.0 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-zoom@1.8.3 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-brush@1.1.6 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-zoom@1.8.3 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-scale-chromatic@1.5.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-brush@1.1.6 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 d3@5.16.0 d3-zoom@1.8.3 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-brush@1.1.6 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-scale@2.2.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-scale-chromatic@1.5.0 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-zoom@1.8.3 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-brush@1.1.6 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-zoom@1.8.3 d3-transition@1.3.2 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-brush@1.1.6 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1
  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-remark-mermaid@1.2.0 mermaid@8.11.2 dagre-d3@0.6.4 d3@5.16.0 d3-zoom@1.8.3 d3-transition@1.3.2 d3-interpolate@1.4.0 d3-color@1.4.1

Overview

d3-color is a Color spaces! RGB, HSL, Cubehelix, Lab and HCL (Lch).

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the rgb() and hrc() functions.

PoC by Yeting Li:

var d3Color = require("d3-color")
// d3Color.rgb("rgb(255,255,255)")

function build_blank(n) {
    var ret = "rgb("
    for (var i = 0; i < n; i++) {
        ret += "1"
    }
    return ret + "!";
}

for(var i = 1; i <= 5000000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_blank(i)
        d3Color.rgb(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 d3-color to version 3.0.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: gatsby-source-git@1.1.0

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-source-git@1.1.0 fast-glob@2.2.7 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

Denial of Service

  • Vulnerable module: node-fetch
  • Introduced through: recompose@0.30.0

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 recompose@0.30.0 fbjs@0.8.17 isomorphic-fetch@2.2.1 node-fetch@1.7.3

Overview

node-fetch is an A light-weight module that brings window.fetch to node.js

Affected versions of this package are vulnerable to Denial of Service. Node Fetch did not honor the size option after following a redirect, which means that when a content size was over the limit, a FetchError would never get thrown and the process would end without failure.

Remediation

Upgrade node-fetch to version 2.6.1, 3.0.0-beta.9 or higher.

References

medium severity

Access Restriction Bypass

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

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 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: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: gatsby-plugin-printer@1.1.1

Detailed paths

  • Introduced through: @unchainedshop/gatsby-theme-apollo-docs@4.3.16 gatsby-plugin-printer@1.1.1 rollup-plugin-node-builtins@2.1.2 browserify-fs@1.0.0 levelup@0.18.6 semver@2.3.2
    Remediation: Open PR to patch semver@2.3.2.

Overview

semver is a semantic version parser used by npm.

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

Overview

npm is a package manager for javascript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The semver module uses regular expressions when parsing a version string. For a carefully crafted input, the time it takes to process these regular expressions is not linear to the length of the input. Since the semver module did not enforce a limit on the version string length, an attacker could provide a long string that would take up a large amount of resources, potentially taking a server down. This issue therefore enables a potential Denial of Service attack. This is a slightly differnt variant of a typical Regular Expression Denial of Service (ReDoS) vulnerability.

Details

<>

Remediation

Update to a version 4.3.2 or greater. From the issue description [2]: "Package version can no longer be more than 256 characters long. This prevents a situation in which parsing the version number can use exponentially more time and memory to parse, leading to a potential denial of service."

References

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 to version 4.3.2 or higher.

References