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CVE-2025-46722

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Date: May 29, 2025

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.

Severity Score

Severity Score

Weakness Type (CWE)

Incomplete Comparison with Missing Factors

CWE-1023

Improper Validation of Consistency within Input

CWE-1288

Top Fix

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Upgrade Version

Upgrade to version vllm - 0.9.0;https://github.com/vllm-project/vllm.git - v0.9.0

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): HIGH
Privileges Required (PR): LOW
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): LOW
Integrity (I): NONE
Availability (A): LOW

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