CVE-2025-46722

vLLM has a Weakness in MultiModalHasher Image Hashing Implementation

State
Published
Severity
4.2 Medium
Published
May 29, 2025
Updated
May 29, 2025
Reserved
Apr 28, 2025

Read the record on cve.org

Description

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.

Scores

CVSSScoreVectorSource
3.14.2 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:LGitHub_M

Weaknesses

  • CWE-1288 Improper Validation of Consistency within Input
  • CWE-1023 Incomplete Comparison with Missing Factors

Affected Products

ProductVersions
vllmvllm-project
  • >= 0.7.0, < 0.9.0Affected

References

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