Vulnerability · Published May 29, 2025 · Assigned by GitHub_M
CVE-2025-46722vLLM has a Weakness in MultiModalHasher Image Hashing Implementation
Medium 4.2
In plain English
A medium-severity security flaw in vllm from vllm-project. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.3% (higher than 27% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official 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 packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | vllm | 0.9.0 | GHSA-c65p-x677-fgj6 |
| PyPI | vllm | 0.9.0 | PYSEC-2025-43 |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| vllm-project | vllm | >= 0.7.0, < 0.9.0 |
Weakness: CWE-1288, CWE-1023 · Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-c65p-x677-fgj6 x_refsource_CONFIRM
- https://github.com/vllm-project/vllm/pull/17378 x_refsource_MISC
- https://github.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5d848 x_refsource_MISC