{
  "id": 6409,
  "url": "https://arxiv.org/abs/2604.02767v1",
  "title": "SentinelAgent: Intent-Verified Delegation Chains for Securing Federal Multi-Agent AI Systems",
  "summary": "When Agent A delegates to Agent B, which invokes Tool C on behalf of User X, no existing framework can answer: whose authorization chain led to this action, and where did it violate policy? This paper introduces SentinelAgent, a formal framework for verifiable delegation chains in federal multi-agent AI systems. The Delegation Chain Calculus (DCC) defines seven properties - six deterministic (authority narrowing, policy preservation, forensic reconstructibility, cascade containment, scope-action",
  "authors": "KrishnaSaiReddy Patil",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": "us",
  "published_at": "2026-04-03T06:25:18.000Z",
  "fetched_at": "2026-07-14T16:32:28.610Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6409",
  "original_url": "https://arxiv.org/abs/2604.02767v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}