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.
| Vendor | Product | Version(s) | CPE |
|---|---|---|---|
| Red Hat | Red Hat AI Inference Server | All Versions ImpactedCNA affecteddefault affected | |
| Red Hat | Red Hat Enterprise Linux AI (RHEL AI) 3 | All Versions ImpactedCNA affecteddefault affected | |
| Red Hat | Red Hat OpenShift AI (RHOAI) | All Versions ImpactedCNA affecteddefault affected | |
| Vllm-Project | VLLM | >= 0.11.0, < 0.24.0CNA affecteddefault unaffected |
CVSS version used by this source: 3.1
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
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