CVE-2026-100651 Details
Description
vLLM before 0.29.0 fails to enforce decoder prompt-length validation on the disaggregated serving endpoint /inference/v1/generate. When the request contains a 'features' (multimodal) payload, vllm/entrypoints/serve/disagg/serving.py builds a multimodal EngineInput directly from the caller-supplied token_ids, and GenerateRequest.token_ids (vllm/entrypoints/serve/disagg/protocol.py) is not checked against model_config.max_model_len. For multimodal processors that report skip_prompt_length_check=True (for example Nemotron Parse, Whisper, and FireRedLID), InputProcessor._validate_prompt_len() returns immediately for both encoder and decoder prompts, so an overlong prompt becomes an EngineCoreRequest and reaches the worker input-batch copy into a fixed max_model_len-wide NumPy row. A client able to reach the endpoint on an affected model configuration can therefore submit an overlong token_ids list to trigger a worker failure and denial of service. Fixed in 0.29.0.
Metrics
CVSS 4.0 Severity and Vector Strings:
CVSS 3.x Severity and Vector Strings:
No data available for CVSS Version 2.0 on this CVE.
No SSVC data is available for this CVE.
References to Advisories, Solutions, and Tools
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Weakness Enumeration
| CWE-ID | CWE Name | Source |
|---|---|---|
| CWE-400 | Uncontrolled Resource Consumption | [email protected] |
Affected Products
No affected product data is available for this CVE.
Change History
1 change record found show changes
| Date | Action | Recorded By |
|---|---|---|
| Sep 26, 2026 | New CVE Received | [email protected] |