| 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) | 2026-10-26 |
| Affected versions | >= 0.16.0, < 0.32.0 from the CVE Program record written by the CNA that assigned the CVE |
| Fixed in | 0.32.0 |
| Weakness | CWE-400CWE-770 |
| CISA KEV | not listed |
NVD description
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.
What to do
- Upgrade vLLM to
0.32.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-115918
- 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