CVE-2026-44223
Modified
Modified - Updated After Analysis
BaseFortify
Publication date: 2026-05-12
Last updated on: 2026-05-15
Assigner: GitHub, Inc.
Description
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.
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| vllm | vllm | From 0.18.0 (inc) to 0.20.0 (exc) |
Helpful Resources
Exploitability
CWE
KEV
| CWE ID | Description |
|---|---|
| CWE-704 | The product does not correctly convert an object, resource, or structure from one type to a different type. |
| CWE-131 | The product does not correctly calculate the size to be used when allocating a buffer, which could lead to a buffer overflow. |
Attack-Flow Graph
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