- CVSS
- MEDIUM · 6.5v3.1CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Published
- 2026-04-06
- Weakness
- CWE-770, CWE-1284
- Source
- nvd.nist.gov/vuln/detail/CVE-2026-34756
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.
References
- https://github.com/vllm-project/vllm/commit/b111f8a61f100fdca08706f41f29ef3548de7380
- https://github.com/vllm-project/vllm/pull/37952
- https://github.com/vllm-project/vllm/security/advisories/GHSA-3mwp-wvh9-7528
- https://access.redhat.com/errata/RHSA-2026:36005
- https://access.redhat.com/errata/RHSA-2026:36006
- https://access.redhat.com/security/cve/CVE-2026-34756
How GTK Cyber trains on this
AI security training at GTK Cyber covers the LLM and ML-pipeline vulnerability classes that vulnerabilities like CVE-2026-34756 fall into. Our hands-on courses are taught by Charles Givre and other practitioners who break and defend production AI systems.