CVE-2026-44223
vLLM: extract_hidden_states speculative decoding crashes server on any request with penalty parameters
Description
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.
INFO
Published Date :
May 12, 2026, 8:16 p.m.
Last Modified :
May 15, 2026, 3:16 p.m.
Remotely Exploit :
Yes !
Source :
[email protected]
CVSS Scores
| Score | Version | Severity | Vector | Exploitability Score | Impact Score | Source |
|---|---|---|---|---|---|---|
| CVSS 3.1 | MEDIUM | [email protected] |
Solution
- Update vLLM to version 0.20.0 or later.
- Avoid using sampling penalty parameters if not updating.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2026-44223.
| URL | Resource |
|---|---|
| https://github.com/vllm-project/vllm/pull/38610 | Issue Tracking Patch |
| https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw | Mitigation Vendor Advisory |
| https://github.com/vllm-project/vllm/pull/38610 | Issue Tracking Patch |
| https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw | Mitigation Vendor Advisory |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-44223 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2026-44223
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2026-44223 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-44223 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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CVE Modified by 134c704f-9b21-4f2e-91b3-4a467353bcc0
May. 15, 2026
Action Type Old Value New Value Added Reference https://github.com/vllm-project/vllm/pull/38610 Added Reference https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw -
Initial Analysis by [email protected]
May. 14, 2026
Action Type Old Value New Value Added CPE Configuration OR *cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* versions from (including) 0.18.0 up to (excluding) 0.20.0 Added Reference Type GitHub, Inc.: https://github.com/vllm-project/vllm/pull/38610 Types: Issue Tracking, Patch Added Reference Type GitHub, Inc.: https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw Types: Mitigation, Vendor Advisory -
New CVE Received by [email protected]
May. 12, 2026
Action Type Old Value New Value Added Description 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. Added CVSS V3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H Added CWE CWE-704 Added CWE CWE-131 Added Reference https://github.com/vllm-project/vllm/pull/38610 Added Reference https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw