CVE-2026-44222Vllm · Vllm
Vulnerability data via NVD (ingested)
vLLM is an inference and serving engine for large language models (LLMs). From 0.6.1 to before 0.20.0, there is a a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on image_grid_thw/video_grid_thw are affected. This vulnerability is fixed in 0.20.0.
External references
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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).
vuln:CVE-2026-44222product:"Vllm Vllm"http.html:"Vllm"More intel sources (5)
vuln:CVE-2026-44222vulnerabilities.cve_id: CVE-2026-44222CVE-2026-44222CVE-2026-44222"CVE-2026-44222" exploit -site:nvd.nist.gov