Agentic Detection Engineering: Autonomous AI Systems for Threat Detection

This academic paper presents a formal exploration of agentic detection engineering, the application of autonomous AI agent systems to the domain of security threat detection. As organizations face increasingly sophisticated and dynamic threat landscapes, traditional rule-based detection approaches struggle to keep pace.

The paper examines:

• Theoretical foundations of agentic systems in security contexts
• Frameworks for building autonomous detection agents
• Integration patterns with existing security infrastructure
• Evaluation methodologies for agentic security systems
• Ethical and operational considerations for autonomous security decision-making

This research bridges the gap between cutting-edge AI agent research and practical security operations, providing both theoretical grounding and actionable guidance for security teams looking to leverage agentic AI.

Read the full paper on SSRN: Agentic Detection Engineering