CVE & CISA-KEV Catalog

CVE-2026-44223

MEDIUM
6.5
CVSS v3
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.

How to fix

Remediation Available
vllmNVD
Affected:>= 0.18.0, < 0.20.0Fixed in:0.20.0CVE-2026-44223derived from NVD

Remediation is compiled from vendor and distribution security advisories. Always confirm against the linked source for your exact version and platform.

CVSS v3 Vector

Exploitability

Attack VectorNetwork
Attack ComplexityLow
Privileges RequiredLow
User InteractionNone
ScopeUnchanged

Impact

ConfidentialityNone
IntegrityNone
AvailabilityHigh

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Exploit Intelligence

0.37%probability of exploitation in 30 days
29thpercentile

Low risk: more likely to be exploited than 29% of all known CVEs.

References

Vendor Advisory1
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Markdown

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HTML

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This product uses NVD data but is not endorsed or certified by the NVD. EPSS scores courtesy of FIRST.org (https://www.first.org/epss). Source: CISA KEV Catalog. Data as of 2026-06-22.