A AegiFlow
MEDIUMCVSS 6.5EPSS 0.3%

CVE-2026-115911

CVE-2026-115911 updated by NVD

Published
2026-10-28
Modified
2026-11-01
EPSS percentile
24%
Sources
github-advisory, nvd

Summary

vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.32.0, authenticated callers can supply a request chat template when no server-side --chat-template is configured, or a malicious model repository can provide a template that is compiled and rendered by tokenizer.apply_chat_template() without a wall-clock timeout, output-size limit, or iteration bound. Rendering runs in a ThreadPoolExecutor with one worker by default, so a nonterminating render can block /v1/responses and other chat-template users after the request ends, while an output-expanding render can exhaust server memory. Harmony models are not affected because they do not use this Jinja path. 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.