CVE-2026-12491
MEDIUMDescription
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.
How to fix
No published remediation has been found for this vulnerability's affected products yet.
Mitigation guidance may be in the linked vendor advisories in the References section below.
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CVSS v3 Vector
Exploitability
Impact
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L
Exploit Intelligence
Low risk: more likely to be exploited than 15% of all known CVEs.
References
Related Vulnerabilities
Other CWE-115 vulnerabilities, ordered by exploit likelihood. View all
| CVE | Severity | CVSS | EPSS | Exploited | Fix |
|---|---|---|---|---|---|
| CVE-2020-27846 | Critical | 9.8 | 4.9% | - | Fix |
| CVE-2018-12116 | High | 7.5 | 4.6% | - | Fix |
| CVE-2018-12123 | Medium | 4.3 | 4.0% | - | Fix |
| CVE-2018-7159 | Medium | 5.3 | 3.6% | - | Fix |
| CVE-2020-29509 | Critical | 9.8 | 2.1% | - | Fix |
| CVE-2020-29510 | Critical | 9.8 | 2.0% | - | - |
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This product uses NVD data but is not endorsed or certified by the NVD. EPSS scores courtesy of FIRST.org (https://www.first.org/epss). Source: CISA KEV Catalog. Data as of 2026-07-07.