Description
vLLM is an inference and serving engine for large language models (LLMs). From 0.1.0 to before 0.19.0, a Denial of Service vulnerability exists in the vLLM OpenAI-compatible API server. Due to the lack of an upper bound validation on the n parameter in the ChatCompletionRequest and CompletionRequest Pydantic models, an unauthenticated attacker can send a single HTTP request with an astronomically large n value. This completely blocks the Python asyncio event loop and causes immediate Out-Of-Memory crashes by allocating millions of request object copies in the heap before the request even reaches the scheduling queue. This vulnerability is fixed in 0.19.0.
Affected products
vllm: vllm
References10
- github.com/vllm-project/vllm/security/advisories/GHSA-3mwp-wvh9… PatchVendor Advisory
- github.com/vllm-project/vllm/commit/b111f8a61f100fdca08706f41f2… Patch
- github.com/vllm-project/vllm/pull/37952 Issue TrackingPatch
- access.redhat.com/errata/RHSA-2026:36005
- access.redhat.com/errata/RHSA-2026:36006
- access.redhat.com/errata/RHSA-2026:57380
- access.redhat.com/errata/RHSA-2026:57387
- access.redhat.com/errata/RHSA-2026:57389
- access.redhat.com/errata/RHSA-2026:57390
- access.redhat.com/errata/RHSA-2026:59144
Metrics
- CVSS 3.1
-
6.5
MEDIUM
Score source: CNA
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - EPSS — exploit probability
- 0% percentile: 39 · as of 12 November 2026
- CWE
- CWE-770CWE-1284
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