Vulnerabilities

30 via 56 paths

Dependencies

378

Source

GitHub

Commit

a92fe2fc

Find, fix and prevent vulnerabilities in your code.

Severity
  • 2
  • 13
  • 13
  • 2
Status
  • 30
  • 0
  • 0

critical severity

Heap-based Buffer Overflow

  • Vulnerable module: sharp
  • Introduced through: sharp@0.27.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2
    Remediation: Upgrade to sharp@0.32.6.

Overview

sharp is a High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP, GIF, AVIF and TIFF images

Affected versions of this package are vulnerable to Heap-based Buffer Overflow when the ReadHuffmanCodes() function is used. An attacker can craft a special WebP lossless file that triggers the ReadHuffmanCodes() function to allocate the HuffmanCode buffer with a size that comes from an array of precomputed sizes: kTableSize. The color_cache_bits value defines which size to use. The kTableSize array only takes into account sizes for 8-bit first-level table lookups but not second-level table lookups. libwebp allows codes that are up to 15-bit (MAX_ALLOWED_CODE_LENGTH). When BuildHuffmanTable() attempts to fill the second-level tables it may write data out-of-bounds. The OOB write to the undersized array happens in ReplicateValue.

Notes:

This is only exploitable if the color_cache_bits value defines which size to use.

This vulnerability was also published on libwebp CVE-2023-5129

Changelog:

2023-09-12: Initial advisory publication

2023-09-27: Advisory details updated, including CVSS, references

2023-09-27: CVE-2023-5129 rejected as a duplicate of CVE-2023-4863

2023-09-28: Research and addition of additional affected libraries

2024-01-28: Additional fix information

Remediation

Upgrade sharp to version 0.32.6 or higher.

References

critical severity

SQL Injection

  • Vulnerable module: sequelize
  • Introduced through: sequelize@5.21.13

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13
    Remediation: Upgrade to sequelize@6.19.1.

Overview

sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.

Affected versions of this package are vulnerable to SQL Injection via the replacements statement. It allowed a malicious actor to pass dangerous values such as OR true; DROP TABLE users through replacements which would result in arbitrary SQL execution.

Remediation

Upgrade sequelize to version 6.19.1 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic was insufficient when extracting tar files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both \ and / characters as path separators. However, \ is a valid filename character on posix systems.

By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location. This can lead to extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite.

Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar archive contained a directory at FOO, followed by a symbolic link named foo, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but not from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the FOO directory would then be placed in the target of the symbolic link, thinking that the directory had already been created.

Remediation

Upgrade tar to version 6.1.7, 5.0.8, 4.4.16 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain two directories and a symlink with names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts. A specially crafted tar archive can include directories with two forms of the path that resolve to the same file system entity, followed by a symbolic link with a name in the first form, lastly followed by a file using the second form. This leads to bypassing node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and extracting arbitrary files into that location.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain .. path portions, and resolving the sanitized paths against the extraction target directory.

This logic is insufficient on Windows systems when extracting tar files that contain a path that is not an absolute path, but specify a drive letter different from the extraction target, such as C:some\path. If the drive letter does not match the extraction target, for example D:\extraction\dir, then the result of path.resolve(extractionDirectory, entryPath) resolves against the current working directory on the C: drive, rather than the extraction target directory.

Additionally, a .. portion of the path can occur immediately after the drive letter, such as C:../foo, and is not properly sanitized by the logic that checks for .. within the normalized and split portions of the path.

Note: This only affects users of node-tar on Windows systems.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity

Improper Filtering of Special Elements

  • Vulnerable module: sequelize
  • Introduced through: sequelize@5.21.13

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13
    Remediation: Upgrade to sequelize@6.29.0.

Overview

sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.

Affected versions of this package are vulnerable to Improper Filtering of Special Elements due to attributes not being escaped if they included ( and ), or were equal to * and were split if they included the character ..

Remediation

Upgrade sequelize to version 6.29.0 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient symlink protection. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain both a directory and a symlink with the same name as the directory. This order of operations results in the directory being created and added to the node-tar directory cache. When a directory is present in the directory cache, subsequent calls to mkdir for that directory are skipped. However, this is also where node-tar checks for symlinks occur. By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location.

Remediation

Upgrade tar to version 3.2.3, 4.4.15, 5.0.7, 6.1.2 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient absolute path sanitization.

node-tar aims to prevent extraction of absolute file paths by turning absolute paths into relative paths when the preservePaths flag is not set to true. This is achieved by stripping the absolute path root from any absolute file paths contained in a tar file. For example, the path /home/user/.bashrc would turn into home/user/.bashrc.

This logic is insufficient when file paths contain repeated path roots such as ////home/user/.bashrc. node-tar only strips a single path root from such paths. When given an absolute file path with repeating path roots, the resulting path (e.g. ///home/user/.bashrc) still resolves to an absolute path.

Remediation

Upgrade tar to version 3.2.2, 4.4.14, 5.0.6, 6.1.1 or higher.

References

high severity

Arbitrary Code Execution

  • Vulnerable module: sqlite3
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2
    Remediation: Upgrade to sqlite3@5.1.5.

Overview

Affected versions of this package are vulnerable to Arbitrary Code Execution via the .ToString() method due to improper sanitization. Exploiting this vulnerability is possible when a binding parameter is a crafted Object and might result in arbitrary JavaScript code execution or DoS.

Workarounds

Ensure sufficient sanitization in the parent application to protect against invalid values being supplied to binding parameters.

Remediation

Upgrade sqlite3 to version 5.1.5 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: sharp@0.27.2 and sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sharp@0.28.0.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sharp@0.28.0.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2 prebuild-install@6.1.4 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sharp@0.29.3.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sqlite3@5.0.3.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-pre-gyp@0.11.0 npmlog@4.1.2 gauge@2.7.4 strip-ansi@3.0.1 ansi-regex@2.1.1
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2 prebuild-install@6.1.4 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sharp@0.29.3.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1
    Remediation: Upgrade to sqlite3@5.0.3.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-pre-gyp@0.11.0 npmlog@4.1.2 gauge@2.7.4 string-width@1.0.2 strip-ansi@3.0.1 ansi-regex@2.1.1

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]* and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*.

PoC

import ansiRegex from 'ansi-regex';

for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = "\u001B["+";".repeat(i*10000);
    ansiRegex().test(attack_str)
    var time_cost = Date.now() - time;
    console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade ansi-regex to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.

References

high severity

Directory Traversal

  • Vulnerable module: moment
  • Introduced through: moment@2.29.1 and modern-logger@1.5.86

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd moment@2.29.1
    Remediation: Upgrade to moment@2.29.2.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd modern-logger@1.5.86 moment@2.29.1

Overview

moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.

Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

  • Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

  • Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside 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 malicious 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

Upgrade moment to version 2.29.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: moment
  • Introduced through: moment@2.29.1 and modern-logger@1.5.86

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd moment@2.29.1
    Remediation: Upgrade to moment@2.29.4.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd modern-logger@1.5.86 moment@2.29.1

Overview

moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the preprocessRFC2822() function in from-string.js, when processing a very long crafted string (over 10k characters).

PoC:

moment("(".repeat(500000))

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 moment to version 2.29.4 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 semver@5.3.0
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

semver is a semantic version parser used by npm.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range, when untrusted user data is provided as a range.

PoC


const semver = require('semver')
const lengths_2 = [2000, 4000, 8000, 16000, 32000, 64000, 128000]

console.log("n[+] Valid range - Test payloads")
for (let i = 0; i =1.2.3' + ' '.repeat(lengths_2[i]) + '<1.3.0';
const start = Date.now()
semver.validRange(value)
// semver.minVersion(value)
// semver.maxSatisfying(["1.2.3"], value)
// semver.minSatisfying(["1.2.3"], value)
// new semver.Range(value, {})

const end = Date.now();
console.log('length=%d, time=%d ms', value.length, end - start);
}

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade semver to version 5.7.2, 6.3.1, 7.5.2 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: sqlite3
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) which will invoke the toString function of the passed parameter. If passed an invalid Function object it will throw and crash the V8 engine.

PoC

let sqlite3 = require('sqlite3').verbose(); 
let db = new sqlite3.Database(':memory:'); 
db.serialize(function() { 
  db.run("CREATE TABLE lorem (info TEXT)"); 
  db.run("INSERT INTO lorem VALUES (?)", [{toString: 23}]);  
});

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade sqlite3 to version 5.0.3 or higher.

References

high severity

SQL Injection

  • Vulnerable module: sequelize
  • Introduced through: sequelize@5.21.13

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13
    Remediation: Upgrade to sequelize@6.21.2.

Overview

sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.

Affected versions of this package are vulnerable to SQL Injection due to an improper escaping for multiple appearances of $ in a string.

Remediation

Upgrade sequelize to version 6.21.2 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: request
  • Introduced through: request-on-steroids@1.1.110, happn-wrapper@1.1.86 and others

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd request-on-steroids@1.1.110 request@2.88.2
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd happn-wrapper@1.1.86 request-on-steroids@1.1.110 request@2.88.2
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd mint-wrapper@1.0.84 request-on-steroids@1.1.110 request@2.88.2
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd tinder-wrapper@1.0.85 request-on-steroids@1.1.110 request@2.88.2
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 request@2.88.2

Overview

request is a simplified http request client.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).

NOTE: request package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.

Remediation

A fix was pushed into the master branch but not yet published.

References

medium severity

Remote Code Execution (RCE)

  • Vulnerable module: sharp
  • Introduced through: sharp@0.27.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sharp@0.27.2
    Remediation: Upgrade to sharp@0.30.5.

Overview

sharp is a High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP, GIF, AVIF and TIFF images

Affected versions of this package are vulnerable to Remote Code Execution (RCE). There is a possible vulnerability in logic that is run only at npm install time when installing the package. If an attacker has the ability to set the value of the PKG_CONFIG_PATH environment variable in a build environment then they might be able to use this to inject an arbitrary command at npm install time. This is not part of any runtime code and does not affect Windows users at all.

Remediation

Upgrade sharp to version 0.30.5 or higher.

References

medium severity
new

Uncontrolled Resource Consumption ('Resource Exhaustion')

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-pre-gyp@0.11.0 tar@4.4.19

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Uncontrolled Resource Consumption ('Resource Exhaustion') due to the lack of folders count validation during the folder creation process. An attacker who generates a large number of sub-folders can consume memory on the system running the software and even crash the client within few seconds of running it using a path with too many sub-folders inside.

Remediation

Upgrade tar to version 6.2.1 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: tough-cookie
  • Introduced through: request-on-steroids@1.1.110, happn-wrapper@1.1.86 and others

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd request-on-steroids@1.1.110 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd happn-wrapper@1.1.86 request-on-steroids@1.1.110 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd mint-wrapper@1.0.84 request-on-steroids@1.1.110 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd tinder-wrapper@1.0.85 request-on-steroids@1.1.110 request@2.88.2 tough-cookie@2.5.0
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 request@2.88.2 tough-cookie@2.5.0

Overview

tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.

Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.

PoC

// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
  "Slonser=polluted; Domain=__proto__; Path=/notauth",
  "https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
  "Auth=Lol; Domain=google.com; Path=/notauth",
  "https://google.com/"
);

//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade tough-cookie to version 4.1.3 or higher.

References

medium severity

Access of Resource Using Incompatible Type ('Type Confusion')

  • Vulnerable module: sequelize
  • Introduced through: sequelize@5.21.13

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13
    Remediation: Upgrade to sequelize@6.28.1.

Overview

sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.

Affected versions of this package are vulnerable to Access of Resource Using Incompatible Type ('Type Confusion') due to improper user-input sanitization, due to unsafe fall-through in GET WHERE conditions.

Remediation

Upgrade sequelize to version 6.28.1 or higher.

References

medium severity

Missing Release of Resource after Effective Lifetime

  • Vulnerable module: inflight
  • Introduced through: sqlite3@5.0.2 and facebook-login-for-robots@1.1.155

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 glob@7.2.3 inflight@1.0.6
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd facebook-login-for-robots@1.1.155 puppeteer@8.0.0 rimraf@3.0.2 glob@7.2.3 inflight@1.0.6
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-pre-gyp@0.11.0 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 fstream@1.0.12 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2 fstream@1.0.12 rimraf@2.7.1 glob@7.2.3 inflight@1.0.6

Overview

Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres function due to improperly deleting keys from the reqs object after execution of callbacks. This behavior causes the keys to remain in the reqs object, which leads to resource exhaustion.

Exploiting this vulnerability results in crashing the node process or in the application crash.

Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.

To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.

PoC

const inflight = require('inflight');

function testInflight() {
  let i = 0;
  function scheduleNext() {
    let key = `key-${i++}`;
    const callback = () => {
    };
    for (let j = 0; j < 1000000; j++) {
      inflight(key, callback);
    }

    setImmediate(scheduleNext);
  }


  if (i % 100 === 0) {
    console.log(process.memoryUsage());
  }

  scheduleNext();
}

testInflight();

Remediation

There is no fixed version for inflight.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: swagger-ui-dist
  • Introduced through: serverful@1.4.90

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd serverful@1.4.90 hapi-swagger@13.1.0 swagger-ui-dist@3.52.5

Overview

swagger-ui-dist is a module that exposes Swagger-UI's entire dist folder as a dependency-free npm module. Use swagger-ui instead, if you'd like to have npm install dependencies for you.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) via the ?url parameter, which was intended to allow displaying remote OpenAPI definitions. This functionality may pose a risk for users who host their own SwaggerUI instances. In particular, including remote OpenAPI definitions opens a vector for phishing attacks by abusing the trusted names/domains of self-hosted instances.

NOTE: This vulnerability has also been identified as: CVE-2021-46708

Remediation

Upgrade swagger-ui-dist to version 4.1.3 or higher.

References

medium severity

Server-side Request Forgery (SSRF)

  • Vulnerable module: swagger-ui-dist
  • Introduced through: serverful@1.4.90

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd serverful@1.4.90 hapi-swagger@13.1.0 swagger-ui-dist@3.52.5

Overview

swagger-ui-dist is a module that exposes Swagger-UI's entire dist folder as a dependency-free npm module. Use swagger-ui instead, if you'd like to have npm install dependencies for you.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) via the ?url parameter, which was intended to allow displaying remote OpenAPI definitions. This functionality may pose a risk for users who host their own SwaggerUI instances. In particular, including remote OpenAPI definitions opens a vector for phishing attacks by abusing the trusted names/domains of self-hosted instances.

NOTE: This vulnerability has also been identified as: CVE-2018-25031

Remediation

Upgrade swagger-ui-dist to version 4.1.3 or higher.

References

medium severity

Information Exposure

  • Vulnerable module: sequelize
  • Introduced through: sequelize@5.21.13

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13
    Remediation: Upgrade to sequelize@6.28.1.

Overview

sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.

Affected versions of this package are vulnerable to Information Exposure due to improper user-input, by allowing an attacker to create malicious queries leading to SQL errors.

Remediation

Upgrade sequelize to version 6.28.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: sequelize@5.21.13 and serverful@1.4.90

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13 validator@10.11.0
    Remediation: Upgrade to sequelize@5.22.5.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd serverful@1.4.90 hapi-swagger@13.1.0 swagger-parser@4.0.2 z-schema@3.25.1 validator@10.11.0

Overview

validator is a library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "111"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }

    return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isSlug(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 validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: sequelize@5.21.13 and serverful@1.4.90

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13 validator@10.11.0
    Remediation: Upgrade to sequelize@5.22.5.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd serverful@1.4.90 hapi-swagger@13.1.0 swagger-parser@4.0.2 z-schema@3.25.1 validator@10.11.0

Overview

validator is a library of string validators and sanitizers.

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

PoC

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

    return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isHSL(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 validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: sequelize@5.21.13 and serverful@1.4.90

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sequelize@5.21.13 validator@10.11.0
    Remediation: Upgrade to sequelize@5.22.5.
  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd serverful@1.4.90 hapi-swagger@13.1.0 swagger-parser@4.0.2 z-schema@3.25.1 validator@10.11.0

Overview

validator is a library of string validators and sanitizers.

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

PoC

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

    return ret+"";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        validator.isEmail(attack_str,{ allow_display_name: true })
        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 validator to version 13.6.0 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: xml2js
  • Introduced through: aws-sdk@2.853.0

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd aws-sdk@2.853.0 xml2js@0.4.19
    Remediation: Upgrade to aws-sdk@2.1354.0.

Overview

Affected versions of this package are vulnerable to Prototype Pollution due to allowing an external attacker to edit or add new properties to an object. This is possible because the application does not properly validate incoming JSON keys, thus allowing the __proto__ property to be edited.

PoC

var parseString = require('xml2js').parseString;

let normal_user_request    = "<role>admin</role>";
let malicious_user_request = "<__proto__><role>admin</role></__proto__>";

const update_user = (userProp) => {
    // A user cannot alter his role. This way we prevent privilege escalations.
    parseString(userProp, function (err, user) {
        if(user.hasOwnProperty("role") && user?.role.toLowerCase() === "admin") {
            console.log("Unauthorized Action");
        } else {
            console.log(user?.role[0]);
        }
    });
}

update_user(normal_user_request);
update_user(malicious_user_request);

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge

  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named __proto__ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to __proto__.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server

  • Web server

  • Web browser

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).

  2. Require schema validation of JSON input.

  3. Avoid using unsafe recursive merge functions.

  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.

  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade xml2js to version 0.5.0 or higher.

References

low severity

Cross-site Scripting (XSS)

  • Vulnerable module: @angular/core
  • Introduced through: @angular/core@4.4.4

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd @angular/core@4.4.4
    Remediation: Upgrade to @angular/core@11.0.5.

Overview

@angular/core is a package that lets you write client-side web applications as if you had a smarter browser. It also lets you use HTML as your template language and lets you extend HTML’s syntax to express your application’s components clearly and succinctly.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) in development, with SSR enabled.

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 @angular/core to version 11.0.5, 11.1.0-next.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tar
  • Introduced through: sqlite3@5.0.2

Detailed paths

  • Introduced through: get-me-a-date@hfreire/get-me-a-date#a92fe2fc17f57f1cb202521fc30aec32a9b4c6cd sqlite3@5.0.2 node-gyp@3.8.0 tar@2.2.2
    Remediation: Upgrade to sqlite3@5.0.3.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When stripping the trailing slash from files arguments, the f.replace(/\/+$/, '') performance of this function can exponentially degrade when f contains many / characters resulting in ReDoS.

This vulnerability is not likely to be exploitable as it requires that the untrusted input is being passed into the tar.extract() or tar.list() array of entries to parse/extract, which would be unusual.

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 tar to version 6.1.4, 5.0.8, 4.4.16 or higher.

References