GHSA-69j4-grxj-j64p
Suggest an improvement- Source
- https://github.com/advisories/GHSA-69j4-grxj-j64p
- Import Source
- https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/11/GHSA-69j4-grxj-j64p/GHSA-69j4-grxj-j64p.json
- JSON Data
- https://api.test.osv.dev/v1/vulns/GHSA-69j4-grxj-j64p
- Aliases
- Published
- 2025-11-20T21:26:24Z
- Modified
- 2025-11-21T19:01:55.288208Z
- Severity
-
- 6.5 (Medium) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H CVSS Calculator
- Summary
- vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`
- Details
-
Summary
The /v1/chat/completions and /tokenize endpoints allow a
chat_template_kwargsrequest parameter that is used in the code before it is properly validated against the chat template. With the rightchat_template_kwargsparameters, it is possible to block processing of the API server for long periods of time, delaying all other requestsDetails
In servingengine.py, the chattemplatekwargs are unpacked into kwargs passed to chatutils.py
apply_hf_chat_templatewith no validation on the keys or values in that chattemplatekwargs dict. This means they can be used to override optional parameters in theapply_hf_chat_templatemethod, such astokenize, 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 servingchat.py and servingtokenization.py call into this
_preprocess_chatmethod ofserving_engine.pyand they both pass inchat_template_kwargs.So, a
chat_template_kwargslike{"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
tokenizeparameter toapply_hf_chat_templatedoes 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 passchat_template_kwargsas unpacked kwargs but instead as a dict, and only unpack them after the logic inapply_hf_chat_templatethat 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
- Database specific
{ "nvd_published_at": "2025-11-21T02:15:43Z", "cwe_ids": [ "CWE-770" ], "github_reviewed_at": "2025-11-20T21:26:24Z", "github_reviewed": true, "severity": "MODERATE" }- References
-
- https://github.com/vllm-project/vllm/security/advisories/GHSA-69j4-grxj-j64p
- https://nvd.nist.gov/vuln/detail/CVE-2025-62426
- https://github.com/vllm-project/vllm/pull/27205
- https://github.com/vllm-project/vllm/commit/3ada34f9cb4d1af763fdfa3b481862a93eb6bd2b
- https://github.com/vllm-project/vllm
- 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
Affected packages
PyPI / vllm
Package
- Name
- vllm
- View open source insights on deps.dev
- Purl
- pkg:pypi/vllm