CVE-2025-24357HIGH 8.8EPSS p46.1%

CVE-2025-24357CVE-2025-24357

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.

Scoring

CVSS 3.18.8 (HIGH)
VectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS0.65% probability of exploitation · percentile 46.1% · 2026-06-18T12:00:27Z
Published2025-01-27
Last modified2025-06-27

Underlying weaknesses· 1

CWE-502

References

  1. https://github.com/vllm-project/vllm/commit/d3d6bb13fb62da3234addf6574922a4ec0513d04
  2. https://github.com/vllm-project/vllm/pull/12366
  3. https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54
  4. https://pytorch.org/docs/stable/generated/torch.load.html

1

TypeTargetConfidenceTier
WeaknessDeserialization of Untrusted Datacwe-5020%live

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Sourced from NVD + FIRST.org EPSS. Curated for EU compliance use cases by Adam Lundqvist, Founder at SQUR.