A Survey on Agentic AI Frameworks for Network Security

The development of the new category of the AI-driven systems called the Agentic AI that represents a paradigm shift in the architectural design of autonomous networked and security-critical systems. so that intelligent agents can perceive their environments, think in complex contexts, plan actions, and autonomously make decisions in continuously evolving and distributed environments. More recent studies have delved into agentic AI in a wide variety of networking and security contexts, such as autonomous network management, flying and edge networks, Open RAN and 6G networks, distributed agent networks, self-healing cybersecurity, closed-loop threat mitigation, multi-agent collaboration, and agentic threat modeling. While these studies represent the potential of agentic AI in enhancing the adaptability, scalability and resilience. The existing literature remains disjointed and has inadequate integration of architectural principles, security, deployment, trust, and governance aspects. This survey contains a holistic and integrated overview of agentic AI frameworks for networked and secure systems. The prior work is systematically examined and categorized it based on the architectural design, deployment environment, level of autonomy, coordination approach, and the integration of security, trust, and governance mechanisms. In order to offer a practical insight, we offer an application-oriented categorization where each framework is categorized into a single main area of operation and providing a clear and non-overlapping representation of the usage of agentic AI systems in practice. The survey focuses on agentic responses to network automation, network monitoring and anomaly detection, autonomous defense and self-healing, automation of the security operations center(SOC), programmable network management, threat modeling, offensive security and trust-aware governance. Hereby, making comparative analysis, we can see common design patterns, strengths, and weaknesses, pointing to open research challenges associated with scalable agent coordination, safe autonomous mitigation, cross-agent trust assessment, explainability, and governance. In general, this survey provides a consolidated reference and research roadmap towards the development of robust, secure and trustworthy agentic AIs based on networking and cybersecurity systems.