ThreatDetect is an AI-powered platform that analyzes employee behavioral data to surface insider threats. Built on XGBoost with Isolation Forest anomaly scoring, it provides both batch organizational analysis and individual employee risk scoring — with SHAP-driven explanations so you always know why a prediction was made.Documentation Index
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Quickstart
Get ThreatDetect running and analyze your first dataset in minutes.
How it works
Understand the detection pipeline: features, model, scoring, and explainability.
CSV batch analysis
Upload an organizational CSV and detect threats across your entire workforce.
Input data schema
Learn exactly which columns your data must contain for accurate predictions.
What ThreatDetect does
ThreatDetect combines machine learning with human-readable explanations to give security teams actionable intelligence — not just a list of flags.Batch organizational scan
Upload a CSV of employee records, run detection, and download results with risk scores for every person.
Single employee lookup
Run a targeted analysis on one employee and see per-feature SHAP explanations driving their risk score.
Explainable predictions
Every prediction comes with SHAP values showing which behavioral features pushed toward malicious vs. normal.
Exploratory data analysis
Explore your dataset interactively — distributions, correlations, scatter plots, and quick anomaly scans.
Get started in three steps
Install dependencies
Clone the repository and install Python requirements with
pip install -r requirements.txt.ThreatDetect requires Python 3.8+ and the pre-trained model file at
AI_Model_Code/insider_threat_model.pkl. See the installation guide for full setup instructions.