PyTorch is vulnerable to memory corruption through its torch.lstm_cell function

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS 4.0

1.9 · CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P · score source

EPSS

• CVE-2025-3001: 0.20% estimated exploitation activity in the next 30 days; percentile 10.19 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.

As published by the source; long descriptions are shortened.

A vulnerability classified as critical was found in PyTorch 2.6.0. This vulnerability affects the function torch.lstmcell. The manipulation leads to memory corruption. The attack needs to be approached locally. The exploit has been disclosed to the public and may be used. A patch is available through commit 999d94b.

Published by the source

31 Mar 2025, 18:31 UTC

Last modified by the source

10 Jun 2026, 18:26 UTC

Source last checked

26 Oct 2026, 13:45 UTC

1. Revision 3 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-qfhq-4f3w-5fph

2. Revision 2 · amended · 25 Oct 2026

   Reviewed OSV alias/range/CVSS4 correction; package source scopes and original publication preserved. No customer finding resolved.

3. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-qfhq-4f3w-5fph

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# Patch Next advisory brief: CVE-2025-3001

Advisory: PyTorch is vulnerable to memory corruption through its torch.lstm_cell function
IDs: CVE-2025-3001, GHSA-qfhq-4f3w-5fph
Record: https://patchnext.com/advisories/cve-2025-3001 (revision 3, source checked 26 Oct 2026, 13:45 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Low (CVSS 1.9)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: torch 2.10.0. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI torch: affected < 2.10.0; fixed in 2.10.0

## Suggested inspection (read-only)
- `python -m pip show torch`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on torch.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://osv.dev/vulnerability/GHSA-qfhq-4f3w-5fph (OSV record GHSA-qfhq-4f3w-5fph lists affected ranges: PyPI torch >=0 <2.10.0 (fixed))
- Verified: https://github.com/advisories/GHSA-qfhq-4f3w-5fph (GitHub-reviewed advisory GHSA-qfhq-4f3w-5fph lists affected ranges: PyPI torch >=0 <2.10.0)

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