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CVE-2025-62609VulnerabilityPublished

CVE-2025-62609: ml-explore mlx · NULL Pointer Dereference

Affects ml-explore mlxSource CVE Database V5

0

Not known to be exploited · CVSS 5.5 Medium : upgrade to 0.29.4 when convenient.

Data as of 26 Oct 2026, 07:57 UTC

CVSS 4.0 base score
5.5Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 34% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 0.29.4
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 21 Nov 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

What to do

Upgrade ml-explore/mlx to 0.29.4.

Affected software

ProductAffectedFixed in
GitHubml-explore/mlxpkg:github/ml-explore/mlxOther threatsAffected
  • <0.29.4
Fixed in
  • 0.29.4

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

European organizations should immediately upgrade all instances of the mlx framework to version 0.29.4 or later, where the NULL pointer dereference vulnerability has been patched. They should audit their ML workflows to identify any components that load GGUF files, especially those accepting files from external or untrusted sources, and implement strict input validation and file integrity checks. Employ sandboxing or containerization for ML applications to contain potential crashes and prevent cascading failures. Monitoring and alerting should be enhanced to detect abnormal application crashes or segmentation faults related to mlx processes. Network-level controls can be used to restrict the sources of GGUF files to trusted repositories or internal systems. Additionally, organizations should review dependency management practices to ensure timely updates of third-party libraries like mlx and gguflib. Finally, incorporating fuzz testing and static analysis in the development lifecycle can help detect similar pointer validation issues proactively.

Description

MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a segmentation fault in mlx::core::load_gguf() when loading malicious GGUF files. Untrusted pointer from external gguflib library is dereferenced without validation, causing application crash. This issue has been patched in version 0.29.4.

References

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