arXiv AI By Genliang Zhu (Accentrust, Georgia Institute of Technology), Chu Wang (Accentrust, University of Illinois Urbana-Champaign)

Versioned Transitive Dependency-Closure Binding and Operation-Time Effect Governance for Agent Skills: ClosureBound

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ClosureBound is a reference monitor that enforces authorization boundaries for agent skills by binding each grant to an exact dependency closure, effect ceiling, purpose, validity, and epochs. It resolves typed graph nodes, normalizes operations into an external‑effect IR, and admits actions only when a joint witness satisfies all bounds, ensuring metadata non‑authority, closure determinism, and other security properties. Empirical evaluation on 549 public skills shows many lack proper dependency declarations, underscoring the need for conservative closure discovery and broader runtime validation.

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arXiv AI
Sep 15

AcquireBound: Runtime Authorization for Resources Acquired by AI Agents

AcquireBound is a runtime authorization framework that ensures AI agents can safely acquire and activate resources such as compute, credentials, and services. It quarantines acquired outputs, resolves their capabilities through authenticated evidence, and activates them only after verifying a manifest, provenance, and relational constraints. The system demonstrates strong safety properties, passing extensive benign and unsafe trace tests across multiple resource classes.

By Genliang Zhu