AI and data stack advisories

Severe, 6 weeks459Projects324

459 severe, 6 weeks · 324 projects

vLLMGHSA-542m-9234-8gvf

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

vLLM

CVE-2026-115911 · Published Oct 28, 2026

Medium6.5
Fix: upgrade to 0.32.0 or later
GitHub advisory

Summary

vLLM renders chat templates by passing the resolved Jinja2 source to tokenizer.apply_chat_template(), which compiles and .render()s it in an ImmutableSandboxedEnvironment. The sandbox prevents code-execution escapes but imposes no wall-clock timeout, no output-size cap, and no nested-loop or binop limit. The render runs in a ThreadPoolExecutor whose max_workers defaults to 1, and CPython worker threads cannot be interrupted. An authenticated API client (or a malicious model repo loaded with trust_remote_code=False) can therefore submit a single short template and permanently wedge all chat-style endpoints (/v1/chat/completions, /v1/responses, /tokenize, /pooling-chat, /invocations-chat) for every tenant until the process is restarted. A string-multiplication variant instead OOM-kills the API-server process. Because of a separately-reported (GHSA-jmjw-q4x3-hmc2) gate omission on /v1/responses, the remote authenticated attacker vector works in **default vllm serve configuration** with no operator opt-in.

Impact

A single authenticated request of <100 bytes permanently denies all chat-style inference (/v1/chat/completions, /v1/responses, /tokenize, /pooling-chat, /invocations-chat) to every tenant of the API-server replica until the operator restarts the process. The string-multiplication variant OOM-kills the...

Affected versions

PackageAffectedFixed in
vllm
PyPI
>= 0.19.0, < 0.32.00.32.0
Details and references

### Summary vLLM renders chat templates by passing the resolved Jinja2 source to `tokenizer.apply_chat_template()`, which compiles and `.render()`s it in an `ImmutableSandboxedEnvironment`. The sandbox prevents code-execution escapes but imposes **no wall-clock timeout, no output-size cap, and no nested-loop or binop limit**. The render runs in a `ThreadPoolExecutor` whose `max_workers` defaults to **1**, and CPython worker threads cannot be interrupted. An authenticated API client (or a malicious model repo loaded with `trust_remote_code=False`) can therefore submit a single short template and permanently wedge **all** chat-style endpoints (`/v1/chat/completions`, `/v1/responses`, `/tokenize`, `/pooling`-chat, `/invocations`-chat) for every tenant until the process is restarted. A string-multiplication variant instead OOM-kills the API-server process. Because of a separately-reported (GHSA-jmjw-q4x3-hmc2) gate omission on `/v1/responses`, the remote authenticated attacker vector works in **default `vllm serve` configuration** with no operator opt-in. ### Impact A single authenticated request of <100 bytes permanently denies all chat-style inference (`/v1/chat/completions`, `/v1/responses`, `/tokenize`, `/pooling`-chat, `/invocations`-chat) to **every tenant** of the API-server replica until the operator restarts the process. The string-multiplication variant OOM-kills the process. In a multi-tenant deployment this is a cross-tenant denial-of-service from any one tenant. From the malicious-model angle, a model repo whose `tokenizer_config.json` carries the hostile template wedges every replica that loads it on the first legitimate chat request, with `trust_remote_code=False`. **Preconditions:** any non-harmony model (`model_type != gpt_oss`); `renderer_num_workers` at its default of 1; for the default-config authenticated API attacker vector, `--chat-template` must be unset (the default because most HF models ship their own). **Blast radius:** API-server process, per replica. Engine/worker processes unaffected by the CPU variant (event loop survives); affected by the memory variant (process OOM). **Persistence:** until process restart. Survives client disconnect. This advisory was fixed in [MR50300](https://github.com/vllm-project/vllm/pull/50300).

CVSS 3.1
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-400, CWE-770, CWE-834
Also known as
CVE-2026-115911

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