BREW-MLX-LM-CVE-2025-3262 (GHSA-489J-G2VX-39WF)
Vulnerability from osv_homebrew – Published: 2026-08-13 17:14 – Updated: 2026-09-10 00:32 – Source websiteA Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the SETTING_RE variable within the transformers/commands/chat.py file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing 'almost matching' payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. The issue is fixed in version 4.51.0.
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "transformers",
"resource_purl": "pkg:pypi/transformers@5.16.1",
"upstream_fixed_in": "4.51.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "mlx-lm",
"purl": "pkg:brew/mlx-lm"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.31.3_2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/transformers@5.16.1",
"name": "transformers",
"resource": "transformers",
"strategy": "registry",
"subject_version": "5.16.1"
}
]
},
"details": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the `SETTING_RE` variable within the `transformers/commands/chat.py` file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing \u0027almost matching\u0027 payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. The issue is fixed in version 4.51.0.",
"id": "BREW-mlx-lm-CVE-2025-3262",
"modified": "2026-09-10T00:32:14Z",
"published": "2026-08-13T17:14:17Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-3262"
},
{
"type": "WEB",
"url": "https://github.com/huggingface/transformers/commit/0720e206c6ba28887e4d60ef60a6a089f6c1cc76"
},
{
"type": "WEB",
"url": "https://github.com/huggingface/transformers/commit/126abe3461762e5fc180e7e614391d1b4ab051ca"
},
{
"type": "PACKAGE",
"url": "https://github.com/huggingface/transformers"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/ecf5ccc4-39e7-4fb3-b547-14a41d31a184"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "Transformers vulnerable to ReDoS attack through its SETTING_RE variable",
"upstream": [
"GHSA-489j-g2vx-39wf",
"CVE-2025-3262",
"PYSEC-2026-1979"
]
}
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.