4.2
Medium
CVE-2025-46722 vLLM is an inference and serving engine for large language models (LLMs)
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.
Affected products and versions
| Product | Affected versions | Fixed in |
|---|---|---|
| vllm 0.7 | 0.7.0 → < 0.9.0 | 0.9.0 |
Other CVEs of vllm
The 121 CVEs of vllm →
CVE-2026-115918
vLLM is an inference and serving engine for large language models
6.5
Medium
CVE-2026-115917
vLLM is an inference and serving engine for large language models
3.4
Low
CVE-2026-115916
vLLM is an inference and serving engine for large language models
6.5
Medium
CVE-2026-115915
vLLM is an inference and serving engine for large language models
8.1
High