Overview
Suta is an API Abuse Detection Engine that leverages Hindsight Agent Memory to identify and prevent malicious API usage patterns. It uses machine learning to analyze request patterns and detect anomalous behavior in real-time.
Key Features
- Real-time API abuse detection using ML models
- Hindsight Agent Memory for pattern recognition
- Express.js backend with WebSocket support
- TensorFlow.js for client-side inference
- MySQL database for attack pattern storage
- Dashboard for monitoring and analytics
Technical Details
Built with Node.js and Express, Suta uses TensorFlow.js for machine learning inference and integrates with Hindsight Agent Memory for contextual pattern analysis. The system processes API requests in real-time, scoring them against known abuse patterns.
Development Challenges
The main challenge was implementing efficient real-time detection without adding significant latency to API requests. The memory-based approach required careful optimization of pattern matching algorithms to balance accuracy with performance.