| Component | vLLM |
| Severity | medium (CVSS 6.5) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Published (NVD) | 2026-05-12 |
| Last modified | 2026-06-22 |
| Affected versions | vllm >= 0.18.0, < 0.20.0 |
| Fixed in | 0.20.0 |
| Weakness | CWE-131CWE-704 |
| CISA KEV | not listed |
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.
What to do
- Upgrade vLLM to
0.20.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-44223
- https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw
- https://github.com/vllm-project/vllm/pull/38610
Read more
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