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This CVE record has been marked for NVD enrichment efforts.
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.
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New CVE Received from Red Hat, Inc.6/17/2026 9:20:04 AM
Action
Type
Old Value
New Value
Added
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.
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Quick Info
CVE Dictionary Entry: CVE-2026-12491 NVD
Published Date: 06/17/2026 NVD
Last Modified: 06/17/2026
Source: Red Hat, Inc.