VulnerabilityAwaiting Analysis

CVE-2026-12491

This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency (tRNS) data, during image processing.

MEDIUM 4.8EPSS 0.24%

Does this matter?

Lower severity and a low EPSS score (0.24%). Track it; it rarely justifies an emergency change on its own.

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.

CVSS 3.1: 4.8 MEDIUMCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
EPSS: 0.24% probability · 15th percentile
CISA KEV: Not listed
Weakness: CWE-115
Source: secalert@redhat.com

References

Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.