HighVulnerability

CVE-2026-31221: PyTorch-Lightning insecure deserialization in checkpoint loading

Source: NVD(opens in a new tab)
Identifier: CVE-2026-31221
Published: May 12, 2026
Record updated: October 9, 2026

Affected: pytorch-lightning <= 2.6.0
Fixed in: No fixed version was stated when the source was last read.
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.4%

Summary

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization flaw (CWE-502) in checkpoint loading. LightningModule.load_from_checkpoint() calls torch.load() without weights_only=True, so arbitrary Python objects can be deserialized via Pickle. A remote attacker who supplies a maliciously crafted checkpoint file can achieve arbitrary code execution when the file is loaded.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

EPSS: 0.4%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 7, 2026.
Disclosure date: May 12, 2026

Weaknesses and techniques

AI threat technique (MITRE ATLAS): AML.T0010

Affected

Packages: pytorch-lightning@<= 2.6.0

Classification

Attack type: Supply chain
Attack sophistication: Trivial
AI component targeted: Framework
Impact: Confidentiality,
Integrity,
Availability,
Safety
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-31221

First tracked: May 12, 2026 at 02:07 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 95% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

pytorch-lightningPyPILLM dependency since 2025-11-05 · 6 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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