CVE-2026-12491EPSS p13.6%

CVE-2026-12491CVE-2026-12491

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.

Scoring

CVSS 4.8 ()
VectorCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
EPSS0.24% probability of exploitation · percentile 13.6% · 2026-10-05T12:00:23Z
Last modified2026-07-07
Sourced from NVD + FIRST.org EPSS. Curated for EU compliance use cases by Adam Lundqvist, Founder at SQUR.