A AegiFlow
MEDIUMCVSS 6.5EPSS 0.4%

CVE-2026-115918

CVE-2026-115918 updated by NVD

Published
2026-10-28
Modified
2026-11-01
EPSS percentile
29%
Sources
github-advisory, nvd

Summary

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.

Affected packages

EcosystemPackageAffected versionsFixed versions
PyPIvllm—0.32.0

Remediation: Upgrade to 0.32.0 or later.

References

Includes data from the GitHub Advisory Database, licensed under CC-BY 4.0.

Includes data from the National Vulnerability Database (NIST). NVD data is in the public domain; this page is not endorsed by NIST.

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EPSS scores provided by the FIRST.org Exploit Prediction Scoring System.