CVE-2026-12491

MEDIUM

Vllm: vllm: image exif rotation & png trns transparency not normalized, causing mismatch between model input and expectations

Title source: cna
STIX 2.1

Description

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.

References (2)

Core 2
Core References
Vdb Entry, X_Refsource_Redhat vdb-entry x_refsource_redhat
https://access.redhat.com/security/cve/CVE-2026-12491
Issue Tracking, X_Refsource_Redhat issue-tracking x_refsource_redhat
RHBZ#2489786
https://bugzilla.redhat.com/show_bug.cgi?id=2489786

Scores

CVSS v3 4.8
EPSS 0.0024
EPSS Percentile 14.9%
Attack Vector NETWORK
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L

CISA SSVC

Vulnrichment
Exploitation none
Automatable no
Technical Impact partial

Details

CWE
CWE-115
Status published
Products (5)
pypi/vllm 0.11.0 - 0.23.0PyPI
Red Hat/Red Hat AI Inference Server
Red Hat/Red Hat Enterprise Linux AI (RHEL AI) 3
Red Hat/Red Hat OpenShift AI (RHOAI)
vllm-project/vLLM 0.11.0 - 0.24.0
Published Jun 17, 2026
Tracked Since Jun 17, 2026