CVE-2026-44222
Gravedad CVSS v3.1:
MEDIA
Tipo:
No Disponible / Otro tipo
Fecha de publicación:
12/05/2026
Última modificación:
12/05/2026
Descripción
*** Pendiente de traducción *** 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.
Impacto
Puntuación base 3.x
6.50
Gravedad 3.x
MEDIA