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.

How to fix CVE-2025-46722

To remediate CVE-2025-46722, upgrade the affected package to a fixed version below.

• —upgrade to 0.9.0 or later
• —upgrade to 99404f53c72965b41558aceb1bc2380875f5d848 or later

Is CVE-2025-46722 being exploited?

Low — EPSS is 0.2%, meaning exploitation activity has not been observed at scale.

Affected packages (2)

• >= 0.7.0, < 0.9.0
• from 0, < 99404f53c72965b41558aceb1bc2380875f5d848 | from 0, < 0.9.0

CVSS scores

References (6)

• ADVISORYnvd.nist.gov/vuln/detail/CVE-2025-46722
• PATCHgithub.com/vllm-project/vllm
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-43.yaml
• WEBgithub.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5d848