PYSEC-2026-4349

Dashboard / Vulnerabilities / PYSEC-2026-4349

PYSEC-2026-4349

Summary:

Details: 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/releases/tag/v0.32.0, https://github.com/vllm-project/vllm/commit/cff08b461e086523cee8bba5bd3c66d302625134, https://github.com/vllm-project/vllm/pull/50300, https://github.com/vllm-project/vllm/security/advisories/GHSA-x567-49g5-p4cf