This site currently shows sample data for demonstration.

Vulnerabilities

CVE-2025-46722 | BDVDB-2026-280523 Detail

vllm-projectvllm

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.

Impact#

Per CVSS v3.1: confidentiality impact low, integrity impact none, availability impact low. Attack vector: network.

Weaknesses#

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

References#

Exploit#

No public exploit known

History#

  1. Version 1Record published in the CVE List.