🛡️ EDR-Hunter Pro

AI-Powered Endpoint Detection & Response

Features

• 🚨 Real-time anomaly detection
• 📊 Streamlit dashboard
• 📱 Telegram alerts (coming soon)
• 📋 Event logging

Objective

Build an AI-powered endpoint detection and response system using machine learning for anomaly detection.

Key Skills Demonstrated

• Machine learning for security (Isolation Forest)
• Real-time anomaly detection
• Streamlit dashboard development
• Telegram bot integration for alerts

My Process

1. Data Collection: Gathered endpoint telemetry (processes, network, CPU, memory)
2. Model Training: Trained Isolation Forest model on normal vs anomalous behavior
3. Dashboard Development: Built real-time monitoring interface with Streamlit
4. Alert Integration: Connected Telegram bot for instant notifications

Tools Used

• Python, Scikit-learn, Pandas, NumPy
• Streamlit, Plotly
• Telegram Bot API

Key Takeaways

• AI can effectively detect behavioral anomalies
• Real-time visualization improves SOC response time
• Instant alerts enable faster incident containment

Quick Start

git clone https://github.com/salhabheba-cyber/EDR-Hunter-Pro.git
cd EDR-Hunter-Pro
pip install -r requirements.txt
streamlit run dashboard.py

Author
Heba Salhab - Beirut, Lebanon