CVE-2025-62426: vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`
Summary The /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chattemplatekwargs parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests Details In servingengine.py, the chattemplatekwargs are unpacked into kwargs…
Published Nov 20, 2025 · Updated Jul 17, 2026
Affected packages
vllm
- Ecosystem
- PyPI
- Affected
- >= 0.5.5, < 0.11.1
- Fixed in
- 0.11.1
- Check
pip show vllm
Advisory details
From the GitHub Advisory Database (CC BY 4.0).
Summary
The /v1/chat/completions and /tokenize endpoints allow a chat_template_kwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chat_template_kwargs parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests
Details
In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py apply_hf_chat_template with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the apply_hf_chat_template method, such as tokenize, changing its default from False to True.
https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814
https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610
Both serving_chat.py and serving_tokenization.py call into this _preprocess_chat method of serving_engine.py and they both pass in chat_template_kwargs.
So, a chat_template_kwargs like {"tokenize": True} makes tokenization happen as part of applying the chat template, even though that is not expected. Tokenization is a blocking operation, and with sufficiently large input can block the API server's event loop, which blocks handling of all other requests until this tokenization is complete.
This optional tokenize parameter to apply_hf_chat_template does not appear to be used, so one option would be to just hard-code that to always be False instead of allowing it to be optionally overridden by callers. A better option may be to not pass chat_template_kwargs as unpacked kwargs but instead as a dict, and only unpack them after the logic in apply_hf_chat_template that resolves the kwargs against the chat template.
Impact
Any authenticated user can cause a denial of service to a vLLM server with Chat Completion or Tokenize requests.
Fix
https://github.com/vllm-project/vllm/pull/27205
Credited to russellb, Isotr0py, DarkLight1337.
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-69j4-grxj-j64p
- https://github.com/vllm-project/vllm/pull/27205
- https://github.com/vllm-project/vllm/commit/3ada34f9cb4d1af763fdfa3b481862a93eb6bd2b
- https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610
- https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814
- https://nvd.nist.gov/vuln/detail/CVE-2025-62426
- https://github.com/advisories/GHSA-69j4-grxj-j64p
- https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2026-2012.yaml
- https://github.com/vllm-project/vllm
- https://pypi.org/project/vllm
How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology
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