CVE-2025-24357

Jan. 27, 2025, 6:15 p.m.

7.5
High

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.

Product(s) Impacted

Product Versions
vLLM library
  • ['before v0.7.0']

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-502
Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.

References

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

Tags

security-advisories@github.com
CWE-502
2025-01-27
CVE-2025-24357

CVSS Score

7.5 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: HIGH
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH

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

    View Vector String

Timeline

Published: Jan. 27, 2025, 6:15 p.m.
Last Modified: Jan. 27, 2025, 6:15 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.