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CVE-2026-12491 Detail

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.


Metrics

NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 4.0 Severity and Vector Strings:

NIST CVSS score
NIST: NVD
N/A
NVD assessment not yet provided.

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URL Source(s) Tag(s)
Red Hat, Inc.
Red Hat, Inc.

Weakness Enumeration

CWE-ID CWE Name Source
CWE-115 Misinterpretation of Input Red Hat, Inc.  

Change History

2 change records found show changes

Quick Info

CVE Dictionary Entry:
CVE-2026-12491
NVD Published Date:
06/17/2026
NVD Last Modified:
06/17/2026
Source:
Red Hat, Inc.