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Advisory details: pypa / vllm/PYSEC-2025-58
Advisory ID pypa/vllm/PYSEC-2025-58
Aliases CVE-2025-24357
GHSA-rh4j-5rhw-hr54
PYSEC-2025-58
Summary 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.
Status Published
Exploitability 0.5
Weighted Severity 7.9
Risk 4.0
Affected and Fixed Packages Package Details
Introduced and Fixed Package Commit Patches Package Commit Patches Details
Weaknesses (0)
There are no known CWE.
System Score Found at
cvssv3.1 8.8 https://github.com/pypa/advisory-database/blob/main/vulns/vllm/PYSEC-2025-58.yaml
Reference id Reference type URL
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
No exploits are available.

No EPSS data available for this advisory.

Patch URL
There are no known patches.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H Found at https://github.com/pypa/advisory-database/blob/main/vulns/vllm/PYSEC-2025-58.yaml
Attack Vector (AV) Attack Complexity (AC) Privileges Required (PR) User Interaction (UI) Scope (S) Confidentiality Impact (C) Integrity Impact (I) Availability Impact (A)

network

adjacent_network

local

physical

low

high

none

low

high

none

required

unchanged

changed

high

low

none

high

low

none

high

low

none

There are no SSVC decisions available.