Bug 2369221 (CVE-2025-46722) - CVE-2025-46722 vllm: vLLM has a Weakness in MultiModalHasher Image Hashing Implementation
Summary: CVE-2025-46722 vllm: vLLM has a Weakness in MultiModalHasher Image Hashing Im...
Keywords:
Status: NEW
Alias: CVE-2025-46722
Product: Security Response
Classification: Other
Component: vulnerability
Version: unspecified
Hardware: All
OS: Linux
medium
medium
Target Milestone: ---
Assignee: Product Security DevOps Team
QA Contact:
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Depends On:
Blocks:
TreeView+ depends on / blocked
 
Reported: 2025-05-29 17:01 UTC by OSIDB Bzimport
Modified: 2025-05-30 13:29 UTC (History)
5 users (show)

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Description OSIDB Bzimport 2025-05-29 17:01:11 UTC
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.


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