{
  "id": 17369,
  "url": "https://arxiv.org/abs/2608.05495v1",
  "title": "PromptShield Home: Ambient Multimodal Prompt Injection Defense for Smart-Home Agents",
  "summary": "Smart-home assistants increasingly use multimodal large language models (MLLMs) that perceive video and audio directly. This raises a safety question specific to the home: can the agent tell a genuine user command from ambient or externally-sourced content, television speech, on-screen text, or an overheard conversation, that merely looks like a command? We introduce PromptShield-Home, a pilot benchmark of realistic smart-home scenarios spanning addressee ambiguity, screen/audio injection, healt",
  "authors": "He Zhang, Feilong Li, Dingning Long, Yilin Cui, Peijun Zhang, Yuewen Zhang, Qianyao Xu, Xinyi Fu",
  "category": "research",
  "topics": "military-security,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-06T00:51:46.000Z",
  "fetched_at": "2026-08-07T05:10:58.501Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17369",
  "original_url": "https://arxiv.org/abs/2608.05495v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}