CVE-2026-44223: vLLM is an inference and serving engine for large language models (LLMs). From 0.18.0 to before 0.20…
- Occurred
- May 12, 2026
- Published
- May 12, 2026
- Source
- NVD CVE
Summary
vLLM is an inference and serving engine for large language models (LLMs). From 0.18.0 to before 0.20.0, the extract_hidden_states speculative decoding proposer in vLLM returns a tensor with an incorrect shape after the first decode step, causing a RuntimeError that crashes the EngineCore process. The crash is triggered when any request in the batch uses sampling penalty parameters (repetition_penalty, frequency_penalty, or presence_penalty). A single request with a penalty parameter (e.g., "repetition_penalty": 1.1) is sufficient to crash the server. This vulnerability is fixed in 0.20.0.
Tags
- CVE
- CVE-2026-44223
- cvss:MEDIUM
Classification
Rationale: vLLM inference engine crash due to tensor shape mismatch in speculative decoding, affecting LLM serving stability.
Classifier: Qwen/Qwen3.5-35B-A3B-FP8