PYSEC-2026-2013 vLLM: Resource-Exhaustion (DoS) through Malicious Jinja Template in OpenAI-Compatible Server

Summary A resource-exhaustion denial-of-service vulnerability exists in multiple endpoints of the OpenAI-Compatible Server due to the ability to specify Jinja templates via the chattemplate and chattemplatekwargs parameters. If an attacker can supply these parameters to the API, they can cause a...

Denial Of Service (DoS)

vllm is vulnerable to Denial Of Service DoS. The vulnerability is due to unrestricted Jinja template injection through the chattemplate and chattemplatekwargs parameters, where crafted templates can trigger unbounded loops or heavy rendering operations, and attackers can exploit this to exhaust C...

vLLM Unlimited Resource Distribution DoS

The vulnerability of the vLLM library for working with large language models is related to the unlimited distribution of resources during the processing of the chattemplatekwargs parameter. Exploiting this vulnerability could allow a malicious actor to cause service failures...

CVE-2025-62426

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, the /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the...

CVE-2025-62426 vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, the /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the...

vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`

Summary The /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chattemplatekwargs parameters, it is possible to block processing of the API server for long...

GHSA-69J4-GRXJ-J64P vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`

Summary The /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chattemplatekwargs parameters, it is possible to block processing of the API server for long...

PT-2025-47650

Name of the Vulnerable Software and Affected Versions vLLM versions 0.5.5 through 0.11.0 Description vLLM is an inference and serving engine for large language models LLMs. The /v1/chat/completions and /tokenize API endpoints accept a chat template kwargs request parameter that is not properly...

vLLM: Resource-Exhaustion (DoS) through Malicious Jinja Template in OpenAI-Compatible Server

Summary A resource-exhaustion denial-of-service vulnerability exists in multiple endpoints of the OpenAI-Compatible Server due to the ability to specify Jinja templates via the chattemplate and chattemplatekwargs parameters. If an attacker can supply these parameters to the API, they can cause a...

PT-2025-41232

Name of the Vulnerable Software and Affected Versions vLLM affected versions not specified Description A resource-exhaustion denial-of-service issue exists in multiple endpoints of the OpenAI-Compatible Server. The server allows users to specify Jinja templates through the chat template and chat...