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CVE-2025-24357

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Date: January 27, 2025

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.

Severity Score

Related Resources (9)

https://github.com/vllm-project/vllm/pull/12366
https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-58.yaml
https://pytorch.org/docs/stable/generated/torch.load.html
https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54
https://nvd.nist.gov/vuln/detail/CVE-2025-24357
https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04
https://github.com/vllm-project/vllm
https://github.com/vllm-project/vllm/releases/tag/v0.7.0
https://www.mend.io/vulnerability-database/CVE-2025-24357

Severity Score

Weakness Type (CWE)

Deserialization of Untrusted Data

CWE-502

Top Fix

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): HIGH
Privileges Required (PR): NONE
User Interaction (UI): REQUIRED
Scope (S): UNCHANGED
Confidentiality (C): HIGH
Integrity (I): HIGH
Availability (A): HIGH

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