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CVE-2025-46722vLLM has a Weakness in MultiModalHasher Image Hashing Implementation

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.

Timeline

  1. ID reserved

    By GitHub_M

  2. · 31 days later

    Published

Changes after publication (a new score, a public exploit, EPSS crossing 1, 10 or 50 %, leaving KEV) are kept since November 2026; earlier ones are not known.

Scores

CVSS scores of CVE-2025-46722, by who scored it
Scored byCVSSScoreVector
GitHub_MCNA (assigner)3.1Medium4.2CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L
NVDNVD · Analyzed3.1High7.3CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
EPSS (exploitation in 30 days)
0.34% · top 72% of all CVEs (12 Nov 2026)
CISA SSVC
Exploitation: none · Automatable: no · Technical impact: partial
Loading the EPSS history…

The list uses the assigner's score when there is one, then CISA's, then NVD's: Medium 4.2.

Affected products

Affected packages

From reviewed advisories of the GitHub Advisory Database.

References

References3

Sources

The same CVE in the primary databases and aggregators, to check against.

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Record last updated .