PYSEC-2025-139
Vulnerability from pysec - Published: 2025-11-21 19:16 - Updated: 2026-05-20 09:19
VLAI
Details
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.
Severity
7.5 (High)
Impacted products
| Name | purl | mlx | pkg:pypi/mlx |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "mlx",
"purl": "pkg:pypi/mlx"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.29.4"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.0.10",
"0.0.11",
"0.0.2",
"0.0.3",
"0.0.4",
"0.0.5",
"0.0.6",
"0.0.7",
"0.0.9",
"0.1.0",
"0.10.0",
"0.11.1",
"0.12.2",
"0.13.0",
"0.13.1",
"0.14.1",
"0.15.2",
"0.16.3",
"0.17.3",
"0.18.1",
"0.19.3",
"0.2.0",
"0.20.0",
"0.21.1",
"0.22.1",
"0.23.2",
"0.24.2",
"0.25.2",
"0.26.1",
"0.26.2",
"0.26.3",
"0.26.5",
"0.27.1",
"0.28.0",
"0.29.0",
"0.29.1",
"0.29.2",
"0.29.3",
"0.3.0",
"0.4.0",
"0.5.1",
"0.6.0",
"0.7.0",
"0.8.1",
"0.9.1"
]
}
],
"aliases": [
"CVE-2025-62609",
"GHSA-j842-xgm4-wf88"
],
"details": "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.",
"id": "PYSEC-2025-139",
"modified": "2026-05-20T09:19:08.526846Z",
"published": "2025-11-21T19:16:02.467Z",
"references": [
{
"type": "EVIDENCE",
"url": "https://github.com/ml-explore/mlx/security/advisories/GHSA-j842-xgm4-wf88"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
]
}
Loading…
Loading…
Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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.
Loading…
Loading…