Search/CVE-2026-12491
● CVE — Medium

CVE-2026-12491

DiscoveredJun 17, 2026UpdatedJul 7, 2026

A flaw was found in vLLM, an open-source library for large language model inference. This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency (tRNS) data, during image processing. When images are converted to RGB, transparency information may be implicitly discarded or remapped, leading to unexpected rendering of transparent pixels and distortion of input content. This can result in the model misinterpreting image content, potentially affecting the integrity of processed data.

CVSS v3.1
4.8 MEDIUM
EPSS
0.24%
probability of exploitation in 30 days
CISA KEV
Not listed
no confirmed exploitation reported
News coverage
0
sources referencing this CVE
Related IOCs
0
seen in the same coverage
CVSS v3.1 Detail
Attack VectorNETWORK
Attack ComplexityHIGH
Privileges RequiredNONE
User InteractionNONE
ScopeUNCHANGED
ConfidentialityNONE
IntegrityLOW
AvailabilityLOW
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
Connections
1 relationships
Timeline
disclosure → media coverage
Jun 17, 2026
Disclosure — published as a CVE record. · last revised by NVD Jul 7, 2026