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

GHSA-63cw-57p8-fm3p pytorch

HIGH

GHSA-63cw-57p8-fm3p is a high-severity (CVSS 8.8) Code Injection vulnerability in pytorch. A fix is available for pytorch — see the affected versions and patch details below.

PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files

Also known asBIT-pytorch-2026-24747CVE-2026-24747PYSEC-2026-1856PYSEC-2026-2286
Published
Jan 27, 2026
Updated
Jul 13, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 18, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • A successful exploit gives an attacker total control of the affected component, not partial access.
  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-63cw-57p8-fm3p.

EPSS Exploitation Probability

via FIRST.org ↗
0.7%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs52th percentile — riskier than 52% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-63cw-57p8-fm3p plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍pytorch

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

Summary

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.

Vulnerability Details

The weights_only=True unpickler failed to properly validate pickle opcodes and storage metadata, allowing:

  1. Heap memory corruption via SETITEM/SETITEMS opcodes applied to non-dictionary types
  2. Storage size mismatch between declared element count and actual data in the archive

Impact

An attacker who can convince a user to load a malicious checkpoint file may achieve arbitrary code execution in the context of the victim's process.

Credit

Ji'an Zhou

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpytorchall versions2.10.0pip install --upgrade 'pytorch==2.10.0'

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, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update pytorch to 2.10.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-63cw-57p8-fm3p is resolved across your whole dependency graph.

  3. Workarounds

    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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-63cw-57p8-fm3p can be triaged on real exposure rather than presence alone.

Tailored to GHSA-63cw-57p8-fm3p. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatImportant
ProductFixed inAdvisory
Red Hat OpenShift AI 2.25rhoai/odh-vllm-gaudi-rhel9:1780069069RHSA-2026:24977

Frequently Asked Questions

### Summary 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. ### Vulnerability Details The `weights_only=True` unpickler failed to properly validate pickle opcodes and storage metadata, allowing: 1. **Heap memory corruption** via `SETITEM`/`SETITEMS` opcodes applied to non-dictionary types 2. **Storage size mismatch** between declared element count and actual data in the archive ### Impact A
O3 Security · Impact-Aware SCA

Is GHSA-63cw-57p8-fm3p in your dependencies?

O3 Security finds GHSA-63cw-57p8-fm3p across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-63cw-57p8-fm3p: pytorch (High 8.8) | O3 Security