SEPTEMBER 22, 2026
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Case File

CVE-2026-44223

MEDIUM · CVSS 6.5 EPSS 0.37% Public Exploit

Source: NVD + CISA KEV + EPSS (historical backfill) · Published 2026-05-12 · Last synced 2026-08-04

CyberRota Analysis

This is a medium severity vulnerability with a CVSS score of 6.5. Public exploit code or proof-of-concept references have been detected in its references.

Public Exploit Signal

A public exploit, PoC, GitHub repository or Metasploit reference was detected for this CVE.

Note: these links are listed for security research and verification purposes only.

CVE
CVE-2026-44223
Severity
MEDIUM
CVSS
6.5
EPSS
0.37%

Original NVD Description

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.

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