CVE-2025-46722
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.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
The vendor-content worker queues fetches as references arrive (check back in a few minutes). Or — if you've already worked around this in production — publish your fix to the community-verified tier.
✚ Propose a mitigation on Community → Mitigations published via the community go through AI scoring + 2 human reviewers + 7-day silent objection window before landing here withsource_tier=community-verified.
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-c65p-x677-fgj6
- https://nvd.nist.gov/vuln/detail/CVE-2025-46722
- https://github.com/vllm-project/vllm/pull/17378
- https://github.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5d848
- https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-43.yaml
- https://github.com/vllm-project/vllm
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.