vLLM allows a malicious model RCE by torch.load in hf_model_weights_iterator
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| vllm-project | vllm | affected |
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EUVD |
EUVD-2025-0192 | 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. |
Github GHSA |
GHSA-rh4j-5rhw-hr54 | vllm: Malicious model to RCE by torch.load in hf_model_weights_iterator |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.893% probability within 30 days)
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Vllm
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| CPEs | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* | |
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Vllm
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| 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. | |
| Title | vLLM allows a malicious model RCE by torch.load in hf_model_weights_iterator | |
| Weaknesses | CWE-502 | |
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| Metrics |
cvssV3_1
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