CVE-2025-46722

HIGH EPSS 18.2%
Published May 29, 20251y ago · Modified Jun 17, 20262w ago
7.3 CVSS 3.1
High
Find Similar
Published May 29, 2025 1y ago
Last Modified Jun 17, 2026 2w ago

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.

CVSS Details

Base Score
7.3
Exploitability
3.9
Impact
3.4
Vector string
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
Attack Vector Network
Attack Complexity Low
Privileges Required None
User Interaction None
Scope Unchanged
Confidentiality Low
Integrity Low
Availability Low

Threat Intelligence

EPSS Exploit Probability
18.2% percentile
Exploit & Patch Status
No Known Exploit
Patch Available

Weaknesses 2

CWE-1023
CWE-1288

Affected Products 1

VendorProductVersionRange
vllmvllm*≥0.7.0  –  <0.9.0

References 3

  • github.com https://github.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5d848
    Patch
  • github.com https://github.com/vllm-project/vllm/pull/17378
    Issue TrackingPatch
  • github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-c65p-x677-fgj6
    Vendor Advisory

Remediation

  • github.com https://github.com/vllm-project/vllm/commit/99404f53c72965b41558aceb1bc2380875f5d848
    Patch
  • github.com https://github.com/vllm-project/vllm/pull/17378
    Issue TrackingPatch