HIGH · 7.5

CVE-2025-24357

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 th...

Vulnerability 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.

CVSS Score

7.5

HIGH

CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
REQUIRED
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH

Affected Products

VendorProductVersions
VllmVllm< 0.7.0

Related Weaknesses (CWE)

References

FAQ

What is CVE-2025-24357?

CVE-2025-24357 is a vulnerability with a CVSS score of 7.5 (HIGH). 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 th...

How severe is CVE-2025-24357?

CVE-2025-24357 has been rated HIGH with a CVSS base score of 7.5/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2025-24357?

Check the references section above for vendor advisories and patch information. Affected products include: Vllm Vllm.