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CVE-2025-46722

vLLM has a Weakness in MultiModalHasher Image Hashing Implementation

Published: May 29, 2025Updated: Jun 24, 2025 Sources: CVE List NVD GHSA BDUCWE-1023

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.

No summary for this CVE yet.

CVSS Vector Breakdown

AV:NAC:HPR:LUI:NS:UC:LI:NA:L
Exploitability
AV:NAttack Vector
Network
AC:HAttack Complexity
High
PR:LPrivileges Required
Low
UI:NUser Interaction
None
Scope
S:UScope
Unchanged
Impact
C:LConfidentiality
Low
I:NIntegrity
None
A:LAvailability
Low

Weaknesses

Affected Products

vllm
oss-projectaka aibrix
vllm-project
oss-projectaka vllm, vllm-project/vllm
PyPI
package-ecosystem

Exploitability

Official Patch Available

References

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