What’s Vulnerable › Vulnerabilities

CVE-2025-24357: vLLM allows a malicious model RCE by torch.load in hf_model_weights_iterator

• Severity: high (CVSS 8.8 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.9% probability of exploitation in the next 30 days
• Public exploit or detection template: none known
• Published: 2025-01-27 · updated 2026-06-17
• Weakness: CWE-502

Description

vLLM is a library for LLM inference and serving. vllm/model_executor/weight_utils.py implements hf_model_weights_iterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weights_only parameter defaults to False. When torch.load loads malicious pickle data, it will execute arbitrary code during unpickling. This vulnerability is fixed in v0.7.0.

Affected products

• vllm-project vllm: before 0.7.0 — fixed in 0.7.0

How to fix

Upgrade to a fixed version: vllm-project vllm 0.7.0. Check the vendor advisory for mitigations.

References

• https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04
• https://github.com/vllm-project/vllm/pull/12366
• https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54
• https://pytorch.org/docs/stable/generated/torch.load.html

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