High severity · published Jan 27, 2025
CVE-2025-24357
vLLM is a library for LLM inference and serving
8.8
CVSS
0.9%
EPSS
No
On KEV
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 vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
Required
Confidentiality
High
Integrity
High
Availability
High
Scope
Unchanged
Exploitation
Is it being used?
Exploit prediction (EPSS)0.9% · higher than 59% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
VL
Vllm · Vllm
before 0.7.0 · source: NVD
References
NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-24357
CVE.org
https://www.cve.org/CVERecord?id=CVE-2025-24357
Patch
https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04
Issue Tracking
https://github.com/vllm-project/vllm/pull/12366
Vendor Advisory
https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54
Technical Description
https://pytorch.org/docs/stable/generated/torch.load.html
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