SentinelAgent: Intent-Verified Delegation Chains for Securing Federal Multi-Agent AI Systems
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
Record details
Published: 3 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (3 April 2026), “SentinelAgent: Intent-Verified Delegation Chains for Securing Federal Multi-Agent AI Systems,” evidence record 6409, https://ethics.ai/record/6409 (originally published by arXiv).
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