CVE & CISA-KEV Catalog

CVE-2025-46722

MEDIUM
4.2
CVSS v3
NVD

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

Remediation Available
vllmNVD
Affected:>= 0.7.0, < 0.9.0Fixed in:0.9.0CVE-2025-46722derived from NVD

Remediation is compiled from vendor and distribution security advisories. Always confirm against the linked source for your exact version and platform.

CVSS v3 Vector

Exploitability

Attack VectorNetwork
Attack ComplexityHigh
Privileges RequiredLow
User InteractionNone
ScopeUnchanged

Impact

ConfidentialityLow
IntegrityNone
AvailabilityLow

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L

Exploit Intelligence

0.27%probability of exploitation in 30 days
18thpercentile

Low risk: more likely to be exploited than 18% of all known CVEs.

References

Vendor Advisory1
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Markdown

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HTML

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This product uses NVD data but is not endorsed or certified by the NVD. EPSS scores courtesy of FIRST.org (https://www.first.org/epss). Source: CISA KEV Catalog. Data as of 2025-06-24.