NeuroEdge is a hybrid intrusion detection framework designed specifically for resource-constrained Edge and IoT environments. It leverages Neuromorphic Computing principles via Spiking Neural Networks (SNNs) to detect network anomalies with high efficiency. The project addresses the severe class imbalance found in standard security datasets (like Bot-IoT) by creating a custom-balanced dataset (DB5) using SMOTE and synthetic data generation. The system features a complete end-to-end pipeline—from live packet capture to inference—deployed on containerized edge devices, capable of detecting attacks like DDoS, Keylogging, and Data Exfiltration in real-time.