Autonomous cyber sovereignty: A dual-control architecture for agentic artificial intelligence in offensive defensive security ecosystems

Agentic artificial intelligence systems autonomous models capable of goal formation, tool invocation, multi-step reasoning, and adaptive self-correction are fundamentally reshaping cybersecurity operations by enabling predictive threat hunting, automated incident response, and large-scale anomaly orchestration. However, these same architectural properties that confer defensive utility simultaneously create unprecedented weaponization vectors, autonomous escalation pathways, and systemic oversight failures that existing governance frameworks are wholly unprepared to address. This paper proposes the Dual-Control Sovereign Agent Architecture, a novel governance and technical control framework integrating a supervisory Artificial Intelligence Sovereignty Layer, Offense–Defense Symmetry Modeling, Autonomous Intent Verification Engine, Agentic Containment Zones with graded autonomy permissions, and a quantitative Cybernetic Escalation Index. The architecture introduces constitutional constraints embedded directly into agent action chains, behavioral cryptographic drift detection, and zero-trust machine identity governance aligned with the National Institute of Standards and Technology Artificial Intelligence Risk Management Framework. Experimental modeling demonstrates that embedding sovereignty constraints reduces unintended agent escalation events by 42% and lowers cross-agent conflict probability by 37% compared to unconstrained autonomous deployments. The Cybernetic Escalation Index provides regulators and security architects with a quantitative systemic risk instrument for measuring autonomous agent interaction hazards across interconnected security ecosystems. This work reframes agentic artificial intelligence in cybersecurity from a capability-centric engineering problem into a sovereignty-centric governance and control theory challenge, proposing a resilient equilibrium between automation utility and systemic risk containment.