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        "state": "PUBLISHED",
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        "dateReserved": "2026-09-26T02:33:07.899Z",
        "datePublished": "2026-09-26T13:23:21.141Z",
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            "datePublic": "2026-09-12T00:00:00.000Z",
            "title": "vllm before 0.29.0 Denial of Service via Decoder Prompt Length Bypass",
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                    "lang": "en",
                    "value": "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."
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                            "description": "Uncontrolled Resource Consumption",
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