vLLM EUVD-2026-58067

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Rated critical severity (CVSS 10.0

vllm-project vllm version v0.6.2 contains a vulnerability in the MessageQueue.dequeue() API function. Rated critical sev

Information exposure in vLLM inference engine versions 0.8.3 to before 0.14.1. Invalid image requests to the multimodal

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Rated high severity (CVSS 7.5), th

vLLM before version 0.14.1 contains a server-side request forgery vulnerability in the MediaConnector class where incons

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Rated medium severity (CVSS 6.5),

Vllm versions up to 0.12.0 is affected by allocation of resources without limits or throttling (CVSS 6.5).

Remote code execution in vLLM 0.10.1 through 0.13.x lets an attacker who controls the model repository or path run arbit

Server-Side Request Forgery in vLLM's multimodal MediaConnector allows remote attackers to coerce the inference server i

Denial of service in vllm 0.19.0's OpenAI-compatible serving path allows remote unauthenticated attackers to exhaust sch

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Rated critical severity (CVSS 9.0)

Remote code execution in vLLM versions prior to 0.22.1 allows attackers to backdoor production LLM inference deployments