CVE-2026-44223Vllm · Vllm
Vulnerability data via NVD (ingested)
vLLM is an inference and serving engine for large language models (LLMs). From 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.
External references
Search for exposed instances
Shodan + Censys queries derived from NVD's CPE data. The vuln tag catches assets Shodan has explicitly linked to this CVE; the product / banner fingerprints find exposed instances even when the vuln tag was never applied (which is common).
vuln:CVE-2026-44223product:"Vllm Vllm"http.html:"Vllm"More intel sources (5)
vuln:CVE-2026-44223vulnerabilities.cve_id: CVE-2026-44223CVE-2026-44223CVE-2026-44223"CVE-2026-44223" exploit -site:nvd.nist.gov