Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍
🐍 PyPI
Not in CISA KEV
HIGH severity

GHSA-75m9-98v2-hjpm

HIGH

GHSA-75m9-98v2-hjpm is a high-severity (CVSS 7.8) remote code execution vulnerability in pytorch-lightning. O3 Security confirms whether GHSA-75m9-98v2-hjpm is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

PyTorch Lightning load_from_checkpoint has an insecure checkpoint deserialization

Also known asCVE-2026-31221PYSEC-2026-3043
Published
May 12, 2026
Updated
Jul 13, 2026
Affected
1 pkg
Patched
None yet
Exploits
None indexed
Exploitation data as of Jul 13, 2026 · OSV.dev, FIRST.org (EPSS)

Real-World Exposure

1 pkg affected
🐍pytorch-lightning

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=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.

Affected Packages

1 total
EcosystemPackageVulnerable rangeFix
🐍PyPIpytorch-lightningall versionsNo fix

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pytorch-lightning. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Remediation status

    No patched version of pytorch-lightning has shipped for GHSA-75m9-98v2-hjpm yet. Where your build allows, override or pin the dependency away from the vulnerable range, and apply any maintainer-recommended mitigation.

  3. Mitigate without a patch

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-75m9-98v2-hjpm is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-75m9-98v2-hjpm. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=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 f
O3 Security · Impact-Aware SCA

Is GHSA-75m9-98v2-hjpm in your dependencies?

O3 detects GHSA-75m9-98v2-hjpm across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-75m9-98v2-hjpm: pytorch-lightning… | O3 Security