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CVE-2025-46722

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CVE-2025-46722

Published: May 29, 2025

Modified: May 29, 2025

PUBLISHED

CVSS v3.1

4.2

MEDIUM

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.

VendorProductVersions

vllm-project

vllm

affected
>= 0.7.0, < 0.9.0

Weaknesses (CWE)

CVSS v3.1 Details

CVSS v3.1 Vector

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L

Attack Vector

Network

Attack Complexity

High

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

Low

Integrity

None

Availability

Low

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