The rising complexity of network traffic in today’s world and the increasing sophistication of cyber threats are the reasons for the requirement of real-time, adaptive monitoring solutions, which are basically systems beyond the traditional static rule-based ones. In order to fill this void, NetScan is proposed as a real-time monitoring framework that is constructed around a multi-layered safety scoring system. The design is in Python 3.11 which is multi-threaded processing and memory management optimized. This combination leads to very low overhead and the maintenance of scalability in high-speed environments. The test at the enterprise-grade test beds has been the experimental evaluation where it is shown that NetScan can achieve a detection accuracy of 98.5%. In addition to that, it can keep the false positive rate at a very low level of 1.2% and can also maintain real-time processing speeds of 10,000 packets per second with just 25% CPU utilization. Thus these outcomes go a long way in proving the efficacy of NetScan, a minimalistic yet strong framework for comprehensive network security monitoring, which gets the best of existing solutions in terms of accuracy, scalability, and efficiency.