CVE-2026-44223
Last modified
CVE-2026-44223 is a medium-severity vulnerability rated 6.5/10 on the CVSS scale. 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. EPSS estimates a 0.37% chance of exploitation in the next 30 days.
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.
Metrics
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness Enumeration
Affected Software
| Vendor | Product | Versions |
|---|---|---|
| Vllm | Vllm | >= 0.18.0, < 0.20.0 |
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
- https://github.com/vllm-project/vllm/pull/38610Issue Tracking, Patch
- https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pwMitigation, Vendor Advisory
Timeline
- Published
- Last Modified
- Status
- Modified
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