PYSEC-2026-2286
Vulnerability from pysec - Published: 2026-01-27 22:15 - Updated: 2026-07-13 05:52
VLAI
Details
PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's weights_only unpickler allows an attacker to craft a malicious checkpoint file (.pth) that, when loaded with torch.load(..., weights_only=True), can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.
Severity
8.8 (High)
Impacted products
| Name | purl | torch | pkg:pypi/torch |
|---|
Aliases
{
"affected": [
{
"ecosystem_specific": {},
"package": {
"ecosystem": "PyPI",
"name": "torch",
"purl": "pkg:pypi/torch"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.10.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"1.0.0",
"1.0.1",
"1.1.0",
"1.10.0",
"1.10.1",
"1.10.2",
"1.11.0",
"1.12.0",
"1.12.1",
"1.13.0",
"1.13.1",
"1.2.0",
"1.3.0",
"1.3.1",
"1.4.0",
"1.5.0",
"1.5.1",
"1.6.0",
"1.7.0",
"1.7.1",
"1.8.0",
"1.8.1",
"1.9.0",
"1.9.1",
"2.0.0",
"2.0.1",
"2.1.0",
"2.1.1",
"2.1.2",
"2.2.0",
"2.2.1",
"2.2.2",
"2.3.0",
"2.3.1",
"2.4.0",
"2.4.1",
"2.5.0",
"2.5.1",
"2.6.0",
"2.7.0",
"2.7.1",
"2.8.0",
"2.9.0",
"2.9.1"
]
}
],
"aliases": [
"CVE-2026-24747",
"GHSA-63cw-57p8-fm3p"
],
"details": "PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch\u0027s `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.pth`) that, when loaded with `torch.load(..., weights_only=True)`, can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.",
"id": "PYSEC-2026-2286",
"modified": "2026-07-13T05:52:12.933057Z",
"published": "2026-01-27T22:15:56.470Z",
"references": [
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2026-24747"
},
{
"type": "WEB",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-24747.json"
},
{
"type": "ADVISORY",
"url": "https://access.redhat.com/errata/RHSA-2026:24977"
},
{
"type": "ADVISORY",
"url": "https://github.com/pytorch/pytorch/releases/tag/v2.10.0"
},
{
"type": "ADVISORY",
"url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-63cw-57p8-fm3p"
},
{
"type": "REPORT",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2433612"
},
{
"type": "REPORT",
"url": "https://github.com/pytorch/pytorch/issues/163105"
},
{
"type": "FIX",
"url": "https://github.com/pytorch/pytorch/163122/commit/954dc5183ee9205cbe79876ad05dd2d9ae752139"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
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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.
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