vLLM Vulnerable to Remote DoS via Special-Token Placeholders

SummaryThis report explains 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...

CVE-2026-44222

A flaw was found in vLLM, an inference and serving engine for large language models LLMs. This vulnerability allows unauthenticated attackers to cause a Denial of Service DoS by supplying image or video placeholder sequences without matching data, leading to an unhandled error and worker...

CVE-2026-44222

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...

CVE-2026-44222 vLLM: Remote DoS via Special-Token Placeholders

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...

CVE-2026-44222 vLLM: Remote DoS via Special-Token Placeholders

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...

CVE-2026-44222

CVE-2026-44222 (vLLM) affects vLLM versions 0.6.1 through 0.19.x where a token-injection vulnerability in multimodal processing allows unauthenticated text prompts containing special tokens to be interpreted as control. When image/video placeholder sequences are provided without corresponding dat...

CVE-2026-44222 vLLM: Remote DoS via Special-Token Placeholders

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...

CVE-2026-44222

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...

vLLM 输入验证错误漏洞

vLLM is an open-source inference and service engine designed for LLM models, featuring high throughput and efficient memory usage. Versions of vLLM prior to 0.6.1 to 0.20.0 contained a vulnerability related to input validation errors. This vulnerability stemmed from token injection issues during...