CVE-2026-12491
Last modified
CVE-2026-12491 is a medium-severity vulnerability rated 4.8/10 on the CVSS scale. 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. EPSS estimates a 0.24% chance of exploitation in the next 30 days.
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
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
Weakness Enumeration
Affected Software
Source: CNA advisory (CVE.org). NVD analysis pending.
| Vendor | Product | Versions |
|---|---|---|
| vllm-project | vLLM | >= 0.11.0, < 0.24.0 |
| Red Hat | Red Hat AI Inference Server | All versions |
| Red Hat | Red Hat Enterprise Linux AI (RHEL AI) 3 | All versions |
| Red Hat | Red Hat OpenShift AI (RHOAI) | All versions |
References
Timeline
- Published
- Last Modified
- Status
- Awaiting Analysis
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