SoK: How Frontier AI Reshapes System-Level Security Risk Dynamics in Critical Infrastructure

Abstract

Frontier artificial intelligence (FAI), encompassing large-scale, general-purpose AI systems, including large language models, multimodal foundation models, and agentic systems, is increasingly integrated into critical infrastructure (CI). This challenges long-standing security assumptions of bounded behavior, segmented networks, component transparency, and human-paced decision-making. Existing AI-security literature typically organizes risks by attack type, lifecycle stage, or asset class, but fails to capture the system-level dynamics, such as how risk emerges, spreads, and is controlled, through which FAI reshapes CI security outcomes. This Systematization of Knowledge (SoK) introduces a five-dimensional risk-dynamics framework that characterizes how FAI reconfigures CI security across the lifecycle: (i) Capability Emergence through new FAI-enabled attack and defense capabilities, (ii) Infiltration Pathways through data, models and AI supply chains, (iii) Cross-System Propagation across interconnected infrastructures and dependencies, (iv) degradation of effective technical and human Control Authority, and (v) strain on institutional Response Capacity under operational pressure. Rather than enumerating threats, the framework identifies recurring mechanisms that jointly determine system-level risk. We further identify a structural mismatch between academic AI-security research and CI operational constraints, and derive a deployment-oriented research agenda grounded in system-level assurance criteria. Collectively, this work shifts attention from model-centric robustness to lifecycle-structured, system-level assurance in interconnected CI environments.