Advisory details:
pypa / vllm/PYSEC-2025-43
| Advisory ID | pypa/vllm/PYSEC-2025-43 |
| Aliases |
CVE-2025-46722
GHSA-c65p-x677-fgj6 PYSEC-2025-43 |
| Summary | 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. |
| Status | Published |
| Exploitability | 0.5 |
| Weighted Severity | 0.0 |
| Risk | |
| Affected and Fixed Packages | Package Details |
| Introduced and Fixed Package Commit Patches | Package Commit Patches Details |
| There are no known CWE. |
| System | Score | Found at |
|---|---|---|
| There are no known severity scores. | ||
No EPSS data available for this advisory.
| Patch URL | |
|---|---|
| There are no known patches. | |
Vector: SSVCv2/E:N/A:N/T:P/P:M/B:A/M:M/D:T/2025-05-29T18:12:29Z/
Decision: Track
Source URL: https://github.com/cisagov/vulnrichment/blob/develop/2025/46xxx/CVE-2025-46722.json
Source Advisory: vulnrichment/CVE-2025-46722
[{'Exploitation': 'none'},
{'Automatable': 'no'},
{'Technical Impact': 'partial'},
{'Mission Prevalence': 'minimal'},
{'Public Well-being Impact': 'material'},
{'Mission & Well-being': 'medium'}]