OCUDU Ecosystem Developer Summit

Operating secure and resilient open-source RAN stacks such as OCUDU remains challenging, particularly for fine-grained runtime observability as well as real-time detection/mitigation of faults and security threats. This presentation introduces an AI-driven Security Operator (AISecOps) framework designed to harden the OCUDU architecture with self-healing and self-defending capabilities.

At its core the AISecOps operator leverages extended Berkeley Packet Filters (eBPF) technology to non-invasively extract real-time RAN-to-Core control plane and KPM telemetry, requiring zero source code modifications. This telemetry feeds a neurosymbolic diagnostic engine that combines deep-learning-based anomaly detection with reasoning-based safety guardrails to detect runtime fault and threat events. Moving beyond passive alerts, a knowledge-grounded agentic AI operator delivers autonomous threat incidents analysis, root-cause diagnostics, and mitigation response.

Attendees will learn how to deploy eBPF into OCUDU for deep security observability, and how agentic AI can automate the security incident handling cycle and execute fully autonomous or human-in-the-loop remediation at the edge.