PyTorch Lightning load_from_checkpoint has an insecure checkpoint deserialization

Exploitation

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

CVSS

7.8 · CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

EPSS

• CVE-2026-31221: 0.39% estimated exploitation activity in the next 30 days; percentile 32.62 (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.

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.loadfromcheckpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weightsonly=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution on the victim's system when the file is loaded.

Published by the source

12 May 2026, 18:30 UTC

Last modified by the source

10 Sep 2026, 17:25 UTC

Source last checked

26 Oct 2026, 13:41 UTC

1. Revision 2 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-75m9-98v2-hjpm

2. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-75m9-98v2-hjpm

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# Patch Next advisory brief: CVE-2026-31221

Advisory: PyTorch Lightning load_from_checkpoint has an insecure checkpoint deserialization
IDs: CVE-2026-31221, GHSA-75m9-98v2-hjpm
Record: https://patchnext.com/advisories/cve-2026-31221 (revision 2, source checked 26 Oct 2026, 13:41 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: High (CVSS 7.8)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor response not established. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI pytorch-lightning: affected <= 2.6.0

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

## Supported action
No complete vendor fix is recorded. Follow the primary source's mitigation guidance and check this record again before closing anything.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on pytorch-lightning.
- 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-75m9-98v2-hjpm (OSV record GHSA-75m9-98v2-hjpm lists affected ranges: PyPI pytorch-lightning >=0 <=2.6.0)
- Verified: https://github.com/advisories/GHSA-75m9-98v2-hjpm (GitHub-reviewed advisory GHSA-75m9-98v2-hjpm lists affected ranges: PyPI pytorch-lightning >=0 <=2.6.0)

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