Wireless networks are increasingly susceptible to network attacks, which are growing in both frequency and severity. This creates significant risks for networks that do not implement adequate security mechanisms. Networks with a large number of connected devices are particularly exposed to threats such as unauthorized access, data breaches, and network congestion. Network Intrusion Detection Systems (NIDS) play a critical role in identifying and preventing malicious activities within a network. However, conventional NIDS solutions are often costly, complex to deploy, and resource-intensive. In this paper, we propose a low-cost, lightweight, and scalable NIDS solution using Raspberry Pi and Snort. The system enables continuous network monitoring through a rule-based detection engine that allows users to define custom rules, such as alert generation, logging, connection dropping, and traffic blocking. Snort is deployed on a Raspberry Pi—a low-power, single-board computer capable of running intrusion detection software with minimal hardware and energy requirements. Once configured, the system detects suspicious network activity and generates real-time alerts displayed on the console. This approach demonstrates how Raspberry Pi and Snort can be effectively combined to enhance network security against malicious attacks. We present the steps involved in installing, configuring, and optimizing Snort on a Raspberry Pi, as well as integrating the device into a distributed NIDS architecture. The proposed solution is evaluated using real-world network traffic data, and the results show that it can accurately detect various types of network intrusions while maintaining low computational overhead.