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 imagegridthw/videogridthw are affected. This vulnerability is fixed in 0.20.0.
{
"osv_generated_from": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/44xxx/CVE-2026-44222.json",
"cna_assigner": "GitHub_M",
"cwe_ids": [
"CWE-129"
]
}