CVE-2026-44223vLLM is an inference and serving engine for large language models (LLMs).
Updated under an hour ago ()
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No exploitation reported and no EPSS estimate yet.
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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.
- CVSS
- 6.5 MEDIUM (v3.1, NVD)CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Weakness (CWE)
- CWE-131, CWE-704
- Known exploited
- Not in CISA's KEV catalog
- EPSS (exploitation in the next 30 days)
- Not loaded for this CVE
- Assigned by
- Not given
- NVD analysis
- Modified
- Record last updated
- Jun 22, 2026
- First seen by InfoSec Signals
- Oct 9, 2026
Affected products
vllm vllm vllm:vllm | from 0.18.0 before 0.20.0 | NVD |
References
- https://github.com/vllm-project/vllm/pull/38610issue-tracking, patch
- https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pwmitigation, vendor-advisory
The CVE record on cve.org NVD's entry
The CVE record is authoritative. Products marked “from the name” were identified from the CNA's free-text names, not a CPE, and are matched less certainly. This product uses the NVD API but is not endorsed or certified by the NVD.