SentinelSandbox is an educational intrusion detection system simulator that demonstrates how security monitoring tools identify suspicious activity in a controlled environment. The app monitors simulated network traffic and host activity, applies rule-based detection logic, and generates alerts when behavior matches common threat patterns such as brute-force attempts, port scanning, abnormal traffic spikes, or repeated requests from a single IP address.
The system is built for educational and portfolio purposes and operates entirely within a safe testing environment where simulated attack scenarios can be triggered to test the detection engine. A real-time dashboard visualizes system status, network activity, and security alerts, allowing users to observe how suspicious behavior is identified and logged. The interface includes live alert panels, an activity feed showing monitored events, system metrics such as CPU and network usage, and controls for triggering simulated attacks. Detection rules are transparent and configurable, allowing users to see exactly how the IDS determines when behavior is suspicious.
By combining network monitoring, rule-based analysis, logging, and interactive visualization, SentinelSandbox provides a clear demonstration of the fundamental principles behind intrusion detection systems used in cybersecurity.
The design was inspired by the visual language of modern cybersecurity platforms to create a sleek and futuristic feel. I focused on a structured, dashboard-driven layout that makes complex security information easy to scan and understand. I focused on a structured dashboard layout that makes complex security information easier to scan, understand, and interact with.
Through this project, I improved my understanding of intrusion detection systems, network monitoring, rule-based threat detection, alert logging, and cybersecurity dashboard design. I also practiced turning a complex security concept into a clear and interactive web experience.
