Executive Summary

Informations
Name CVE-2025-24357 First vendor Publication 2025-01-27
Vendor Cve Last vendor Modification 2025-06-27

Security-Database Scoring CVSS v3

Cvss vector : CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Overall CVSS Score 8.8
Base Score 8.8 Environmental Score 8.8
impact SubScore 5.9 Temporal Score 8.8
Exploitabality Sub Score 2.8
 
Attack Vector Network Attack Complexity Low
Privileges Required None User Interaction Required
Scope Unchanged Confidentiality Impact High
Integrity Impact High Availability Impact High
Calculate full CVSS 3.0 Vectors scores

Security-Database Scoring CVSS v2

Cvss vector :
Cvss Base Score N/A Attack Range N/A
Cvss Impact Score N/A Attack Complexity N/A
Cvss Expoit Score N/A Authentication N/A
Calculate full CVSS 2.0 Vectors scores

Detail

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.

Original Source

Url : http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2025-24357

CWE : Common Weakness Enumeration

% Id Name
100 % CWE-502 Deserialization of Untrusted Data

CPE : Common Platform Enumeration

TypeDescriptionCount
Application 1

Sources (Detail)

https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec...
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
Source Url

Alert History

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0
1
Date Informations
2025-06-28 00:20:47
  • Multiple Updates
2025-01-27 21:20:30
  • First insertion