CVE-2026-12491
Received
Received - Intake
Improper Image Metadata Handling in vLLM
Publication date: 2026-06-17
Last updated on: 2026-06-17
Assigner: Red Hat, Inc.
Description
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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Affected Vendors & Products
Currently, no data is known.
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Exploitability
| CWE ID | Description |
|---|---|
| CWE-115 | The product misinterprets an input, whether from an attacker or another product, in a security-relevant fashion. |