CVE-2026-12491
Vulnerability data via NVD (ingested)
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.
External references
Search for exposed instances
Shodan + Censys queries derived from NVD's CPE data. The vuln tag catches assets Shodan has explicitly linked to this CVE; the product / banner fingerprints find exposed instances even when the vuln tag was never applied (which is common).
More intel sources (5)
vuln:CVE-2026-12491vulnerabilities.cve_id: CVE-2026-12491CVE-2026-12491CVE-2026-12491"CVE-2026-12491" exploit -site:nvd.nist.gov