Ha Test

Inspiration We noticed that Blue Team analysts often spend more time sifting through noisy logs than actually responding to real threats. We wanted to build something that cuts through that noise and helps defenders act faster. What it does Ha Test collects and analyzes security logs in real time, flags suspicious activity based on defined rules and patterns, and presents findings in a clear, actionable dashboard. It helps analysts prioritize alerts and speeds up the investigation process during potential incidents. How we built it We built the backend to ingest and parse log data, applied detection logic to identify anomalies, and connected it to a frontend dashboard for visualization. We focused on keeping the pipeline lightweight so it could integrate with existing security infrastructure. Challenges we ran into Handling large volumes of log data without slowing down detection was a major challenge. We also had to balance sensitivity in our detection rules to avoid overwhelming analysts with false positives while still catching real threats. Accomplishments that we're proud of We're proud of building a working pipeline that goes from raw log ingestion to a usable alert within a short timeframe. Getting real-time detection working reliably, even under time constraints, felt like a big win for the team. What we learned We learned a lot about the tradeoffs between detection accuracy and performance, and how critical good data structuring is for fast analysis. We also gained hands-on experience with how real Blue Team workflows operate. What's next for Ha Test Next, we want to add machine learning-based anomaly detection, expand integrations with more SIEM tools, and improve the dashboard with better filtering and historical trend analysis to help teams spot patterns over time.

Built With

• javascript
• python