{
  "id": 583,
  "url": "https://arxiv.org/abs/2606.26627v1",
  "title": "Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents",
  "summary": "Large language model agents increasingly query databases, search document collections, call external APIs, remember past interactions, and act on a user's behalf. As they move from answering questions to operating over sensitive data, privacy becomes harder to enforce. An agent touches many data sources, runs multi-step workflows, keeps state across sessions, and acts with delegated permissions. Sensitive information can therefore leak not only through its final answer but through the queries it",
  "authors": "Nada Lahjouji, Ashwin Gerard Colaco",
  "category": "research",
  "topics": "privacy-surveillance,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-25T05:44:18.000Z",
  "fetched_at": "2026-07-14T14:14:37.249Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/583",
  "original_url": "https://arxiv.org/abs/2606.26627v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}