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CVE-2025-24357

HIGHCVSS 8.8/10EPSS 0.69%

Last modified

CVE-2025-24357 is a high-severity vulnerability rated 8.8/10 on the CVSS scale. 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. EPSS estimates a 0.69% chance of exploitation in the next 30 days.

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.

Metrics

CVSS 3.1
8.8/10

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

EPSS Probability
0.69%

48.3th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

Affected Software

VendorProductVersions
VllmVllm< 0.7.0

References

Timeline

Published
Last Modified
Status
Analyzed

Frequently Asked Questions

What is 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 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.
How severe is CVE-2025-24357?
CVE-2025-24357 has a CVSS score of 8.8/10 (HIGH severity). The EPSS model estimates a 0.69% probability of exploitation in the next 30 days.
How do I fix CVE-2025-24357?
Check the vendor references and advisories linked above for patched versions and mitigation guidance. You can also run a Strix scan to test if your systems are affected.

Are you affected by CVE-2025-24357?

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Source: NVD / NIST