| 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) | 2026-10-05 |
| Last modified | 2026-10-08 |
| Affected versions | vllm < 0.30.0 |
| Fixed in | 0.30.0 |
| Weakness | CWE-20CWE-248CWE-755 |
| CISA KEV | not listed |
NVD description
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.
What to do
- Upgrade vLLM to
0.30.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-105757
- https://github.com/vllm-project/vllm/security/advisories/GHSA-85xf-c7hm-whqw
- https://github.com/vllm-project/vllm/commit/c55e15a44ec4127832d4a86928a356fdd9e68dbd
- https://github.com/vllm-project/vllm/pull/51450
- https://github.com/vllm-project/vllm/releases/tag/v0.30.0
Read more
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