Incomplete Comparison with Missing Factors Affecting py3.10-vllm-cuda-11.8 package, versions <0.9.0-r0


Severity

Recommended
0.0
high
0
10

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Threat Intelligence

EPSS
0.34% (27th percentile)

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  • Snyk IDSNYK-CHAINGUARDLATEST-PY310VLLMCUDA118-10263066
  • published29 May 2025
  • disclosed29 May 2025

Introduced: 29 May 2025

CVE-2025-46722  (opens in a new tab)
CWE-1023  (opens in a new tab)
CWE-1288  (opens in a new tab)

How to fix?

Upgrade Chainguard py3.10-vllm-cuda-11.8 to version 0.9.0-r0 or higher.

NVD Description

Note: Versions mentioned in the description apply only to the upstream py3.10-vllm-cuda-11.8 package and not the py3.10-vllm-cuda-11.8 package as distributed by Chainguard. See How to fix? for Chainguard relevant fixed versions and status.

vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.

CVSS Base Scores

version 3.1