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Advisory details: vulnrichment / CVE-2026-44223
Advisory ID vulnrichment/CVE-2026-44223
Aliases
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.
Status Published
Exploitability 0.5
Weighted Severity 0.0
Risk
Affected and Fixed Packages Package Details
Introduced and Fixed Package Commit Patches Package Commit Patches Details
Weaknesses (2)
CWE-131 Incorrect Calculation of Buffer Size
CWE-704 Incorrect Type Conversion or Cast
System Score Found at
cvssv3.1 6.5
ssvc Track
Reference id Reference type URL
38610 Other https://github.com/vllm-project/vllm/pull/38610
GHSA-83vm-p52w-f9pw Other https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw
No exploits are available.

No EPSS data available for this advisory.

Patch URL
There are no known patches.
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H Found at None
Attack Vector (AV) Attack Complexity (AC) Privileges Required (PR) User Interaction (UI) Scope (S) Confidentiality Impact (C) Integrity Impact (I) Availability Impact (A)

network

adjacent_network

local

physical

low

high

none

low

high

none

required

unchanged

changed

high

low

none

high

low

none

high

low

none
Vector: SSVCv2/E:P/A:N/T:P/P:M/B:A/M:M/D:T/2026-05-15T14:44:05Z/ Found at None

Vector: SSVCv2/E:P/A:N/T:P/P:M/B:A/M:M/D:T/2026-05-15T14:44:05Z/

Decision: Track

Source URL: https://github.com/cisagov/vulnrichment/blob/develop/2026/44xxx/CVE-2026-44223.json

Source Advisory: vulnrichment/CVE-2026-44223

View SSVC decision tree 
[{'Exploitation': 'poc'},
 {'Automatable': 'no'},
 {'Technical Impact': 'partial'},
 {'Mission Prevalence': 'minimal'},
 {'Public Well-being Impact': 'material'},
 {'Mission & Well-being': 'medium'}]