CVE-2025-46722
Published: 29 May 2025
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
- 🇪🇺 ENISA EUVD: EUVD-2025-16188
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
Mitigating Controls
No mitigating controls mapped yet. The per-CVE control annotator has not reached this CVE.