MEDIUM 6.5 NVD
CVE-2026-115918
vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place
vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0.
References
- https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134
- https://github.com/vllm-project/vllm/pull/50300
- https://github.com/vllm-project/vllm/releases/tag/v0.32.0
- https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf
This medium severity vulnerability with a CVSS score of 6.5 was published on 2026-10-26 via NVD.
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