CVEvulnerability

CVE-2025-46722

7.3 HIGH Published 2025-05-29 Modified 2026-06-17 Official page ↗
Status
Analyzed
Published
2025-05-29
Last modified
2026-06-17
Assigner
[email protected]
CVSS 3.1 ([email protected])
4.2 MEDIUM — CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L
CVSS 3.1 ([email protected])
7.3 HIGH — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
Weaknesses
CWE-1023, CWE-1288

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.

Affected configurations

• vllm vllm (>= 0.7.0 < 0.9.0)

Related

Weakness · CWE (2)

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

References