Cyber Resilience

CVE-2025-46722

Medium

Published: 29 May 2025

Published
29 May 2025
Modified
24 June 2025
KEV Added
Patch
CVSS Score v3.1 4.2 CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L
EPSS Score 0.0023 46.1th percentile
Risk Priority 9 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2025-46722 is a medium-severity Incomplete Comparison with Missing Factors (CWE-1023) vulnerability in Vllm Vllm. Its CVSS base score is 4.2 (Medium).

Operationally, ranked at the 46.1th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as NLP and Transformers; in the Data-Related Vulnerabilities risk domain.

EU & UK References

Vulnerability details

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,…

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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.

CWE(s)

AI Security AnalysisAI

AI Category
NLP and Transformers
Risk Domain
Data-Related Vulnerabilities
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: llms, vllm

Related Threats

Affected Assets

vllm
vllm
0.7.0 — 0.9.0

Mitigating Controls

No mitigating controls mapped yet. The per-CVE control annotator has not reached this CVE.

References