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CVE-2025-22150: Use of Insufficiently Random Values in undici

January 21, 2025

Undici fetch() uses Math.random() to choose the boundary for a multipart/form-data request. It is known that the output of Math.random() can be predicted if several of its generated values are known.

If there is a mechanism in an app that sends multipart requests to an attacker-controlled website, they can use this to leak the necessary values. Therefore, An attacker can tamper with the requests going to the backend APIs if certain conditions are met.

References

  • blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f
  • github.com/advisories/GHSA-c76h-2ccp-4975
  • github.com/nodejs/undici
  • github.com/nodejs/undici/blob/8b06b8250907d92fead664b3368f1d2aa27c1f35/lib/web/fetch/body.js
  • github.com/nodejs/undici/commit/711e20772764c29f6622ddc937c63b6eefdf07d0
  • github.com/nodejs/undici/commit/c2d78cd19fe4f4c621424491e26ce299e65e934a
  • github.com/nodejs/undici/commit/c3acc6050b781b827d80c86cbbab34f14458d385
  • github.com/nodejs/undici/security/advisories/GHSA-c76h-2ccp-4975
  • hackerone.com/reports/2913312
  • nvd.nist.gov/vuln/detail/CVE-2025-22150

Code Behaviors & Features

Detect and mitigate CVE-2025-22150 with GitLab Dependency Scanning

Secure your software supply chain by verifying that all open source dependencies used in your projects contain no disclosed vulnerabilities. Dependency Scanning using SBOM also detects vulnerabilities from proprietary advisories that this site does not include. Learn more about Dependency Scanning using SBOM →

Affected versions

All versions starting from 4.5.0 before 5.28.5, all versions starting from 6.0.0 before 6.21.1, all versions starting from 7.0.0 before 7.2.3

Fixed versions

  • 5.28.5
  • 6.21.1
  • 7.2.3

Solution

Upgrade to versions 5.28.5, 6.21.1, 7.2.3 or above.

Impact 6.8 MEDIUM

CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:N

Learn more about CVSS

Weakness

  • CWE-330: Use of Insufficiently Random Values

Source file

npm/undici/CVE-2025-22150.yml

Spotted a mistake? Edit the file on GitLab.

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