CVE-2025-32434 — torch
Fix: pytorch/pytorch@8d4b8a9CVE-2025-32434 is a Deserialization of Untrusted Data vulnerability in torch. A fix is available for torch — see the affected versions and patch details below.
PyTorch: `torch.load` with `weights_only=True` leads to remote code execution
Exploitation Status
No confirmed exploitation observed yet
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
- 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 CVE-2025-32434.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
Real-World Exposure
torchReal-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
Description
I found a Remote Command Execution (RCE) vulnerability in PyTorch. When loading model using torch.load with weights_only=True, it can still achieve RCE.
Background knowledge
https://github.com/pytorch/pytorch/security
As you can see, the PyTorch official documentation considers using torch.load() with weights_only=True to be safe.
Since everyone knows that weights_only=False is unsafe, so they will use the weights_only=True to mitigate the seucirty issue.
But now, I just proved that even if you use weights_only=True, it can still achieve RCE.
Credit
This vulnerability was found by Ji'an Zhou.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | torch | all versions | 2.6.0pip install --upgrade 'torch==2.6.0' |
Affected Products
pytorchlinuxfoundationDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for torch, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update torch to 2.6.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2025-32434 is resolved across your whole dependency graph.
Workarounds
Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.
Frequently Asked Questions
Is CVE-2025-32434 in your dependencies?
Find it across PyPI, including transitive dependencies.