Modern cybersecurity has long relied on anomaly detection, assuming malicious activity deviates from normal system behavior. However, AI-driven attacks challenge this foundational model. This presentation explores the concept of the “clean attack,” where adversaries leverage AI agents to execute sequences of legitimate actions—using valid credentials, trusted workflows, and authorized interactions—making malicious intent indistinguishable from normal operations. As a result, traditional detection mechanisms such as signature-based systems, static rules, and threshold alerts become ineffective. Through real-world examples, including large-scale breaches, the limitations of anomaly-centric security are highlighted. The talk introduces a shift toward intent-based security, focusing on understanding the purpose behind actions rather than solely monitoring behavior. By incorporating behavioral sequencing, contextual awareness, workflow validation, and runtime decision analysis, this approach redefines security from static enforcement to dynamic reasoning. The framework aims to address the growing challenge of AI-powered threats and establish a foundation for resilient, adaptive cybersecurity systems.