Skip to main content
← All vulnerabilities
CVE-2026-115911EUVD-2026-109996GHSA-542M-9234-8GVFPYSEC-2026-4344

vLLM: DoS via unbounded chat_template Jinja2 rendering exhausts the renderer thread pool

Published
Last modified
published
Not listed in CISA KEV
Fix
Fixed in 0.32.0
None on Exploit-DB, Metasploit or GitHub
  • Exploitation: none
  • Automatable: no
  • Technical impact: partial

Summary

vLLM, an open-source engine for serving large language models, is affected. A caller with access, or a malicious model repository, can supply a chat template that runs forever or produces huge output, which can stop the server from handling chat requests or exhaust its memory.

Summarized by anthropic/claude-haiku-5.5. Verify details against the original sources.

Read the original description

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.

Timeline

  1. CVE published
  2. First seen by cve.now
  3. CISA SSVC assessment

    Exploitation: none · Automatable: no · Technical impact: partial

  4. Record last updated

Affected versions

  • vllm-project vllm

    From 0.19.0 · fixed in 0.32.0

  • vllmPyPI

    From 0.19.0 · fixed in 0.32.0

References 4

GitHub · vllm-project/vllm