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February 20, 20260 citationsOpen Access

ACC: Agent Capability Control v1.0.0 - Declarative Authorization for Autonomous AI

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AAdaRHRudi Heydra

Key Points

  • The research aims to present a security framework for managing permissions in autonomous AI systems using a declarative approach.
  • Developed Agent Capability Control (ACC) framework for AI ecosystems.
  • Introduced a three-layer security model combining role-based permissions, behavioral constraints, and per-skill capability grants.
  • Implemented monotonic attenuation allowing sub-agents restricted access to the parent agent's permissions.
  • Integrated Delegation Capability Tokens for secure cryptographic permission transfers.
  • Demonstrated improved security through layered authorization in AI agents.
  • Showed that monotonic attenuation effectively limits permission propagation to sub-agents.
  • Provided a framework for provable and auditable agent authorization.

Abstract

Agent Capability Control (ACC) is a declarative authorization framework for AI agent ecosystems. It provides three-layer security through RBAC.md (role-based permissions), SOUL.md (behavioral constraints), and SKILL.md (per-skill capability grants). Key innovations include monotonic attenuation (sub-agents can only receive subsets of parent permissions) and Delegation Capability Tokens (DCTs) for cryptographic permission transfer. ACC integrates with FDAA (File-Driven Agent Architecture) to provide provable, auditable agent authorization.

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Cite This Study

Ada et al. (2026) studied this question.

synapsesocial.com/papers/6997fa6dad1d9b11b3453970https://doi.org/10.5281/zenodo.18676278
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