Vulnerability 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.
CVSS Score
MEDIUM
Affected Products
| Vendor | Product | Versions |
|---|---|---|
| Vllm | Vllm | >= 0.7.0, < 0.9.0 |
Related Weaknesses (CWE)
References
- https://github.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5Patch
- https://github.com/vllm-project/vllm/pull/17378Issue TrackingPatch
- https://github.com/vllm-project/vllm/security/advisories/GHSA-c65p-x677-fgj6Vendor Advisory
FAQ
What is CVE-2025-46722?
CVE-2025-46722 is a vulnerability with a CVSS score of 4.2 (MEDIUM). 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 secur...
How severe is CVE-2025-46722?
CVE-2025-46722 has been rated MEDIUM with a CVSS base score of 4.2/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2025-46722?
Check the references section above for vendor advisories and patch information. Affected products include: Vllm Vllm.