AI-Powered Data Breach Hub

Led the design and delivery of an open-access AI-powered data breach intelligence platform that aggregates and normalizes 3,100+ public breach and security incident reports per year. The system automatically collects breach information from multiple sources, processes it using advanced GenAI techniques, and provides comprehensive analytics through an interactive dashboard to help security analysts understand threat patterns and benchmark organizational risk exposure.

August 2025 - December 2025

Live Demo

Python TypeScript Next.js Tailwind CSS FastAPI Docker AWS S3 Lambda Redis ScrapeGraphAI MongoDB ElasticSearch Kibana Pytest Ruff GitHub Actions

The Challenge

Security analysts lack access to comprehensive, real-time threat intelligence for understanding cybersecurity breach patterns across industries. Existing breach data is fragmented across multiple sources, inconsistently formatted, and often contains sensitive PII that limits its use. Organizations cannot effectively benchmark their security posture or identify emerging threat patterns without labor-intensive manual research.

The Solution

Led the design and delivery of an AI-powered data breach intelligence platform in collaboration with Amazon. The system aggregates and normalizes 3,100+ public breach and security incident reports annually, using GenAI pipelines for automatic classification and analysis. The platform features a privacy-safe AWS architecture ensuring 100% PII-free ingestion, with comprehensive analytics delivered through an interactive dashboard powered by Elasticsearch and Kibana.

Technical Highlights

Architected scalable AWS infrastructure using Lambda, S3, and Redis for high-throughput data processing and storage
Implemented GenAI classification pipelines using ScrapeGraphAI for intelligent breach categorization and threat analysis
Built polyglot storage layer with MongoDB for documents and Elasticsearch for real-time analytics and search
Designed privacy-safe data collection ensuring 100% PII-free ingestion with legally-sourced, ethical data acquisition
Created interactive Kibana dashboards enabling sector-specific threat analysis and trend visualization

Key Results & Impact

Aggregates 3,100+ security incidents per year enabling comprehensive threat landscape analysis

Detected +42% ransomware growth in universities and +58% data-theft disclosures in hospitals through GenAI analysis

Maintains 100% PII-free data ingestion ensuring privacy compliance and ethical data handling

Delivers real-time analytics through Elasticsearch enabling instant threat pattern identification

Provides horizontal scalability supporting growing data volumes without architecture changes

Business Impact

This platform transforms how security teams understand and respond to the evolving threat landscape. By providing real-time, AI-powered breach intelligence, organizations can make data-driven security decisions and benchmark their exposure against industry peers. The project demonstrates expertise in cloud architecture, GenAI applications, and building production data pipelines for enterprise security use cases.

Key Achievements

Architected a data intelligence platform aggregating 3.1k+ incidents per year, enabling real-time sector and threat analysis

Deployed GenAI pipelines detecting +42% ransomware growth in universities and +58% data-theft disclosures in hospitals

Provisioned a scalable, privacy-safe AWS architecture ensuring 100% PII-free ingestion and high-throughput analytics

Implemented end-to-end AI data pipeline covering GenAI classification, polyglot storage, and Elasticsearch analytics

Engineered ethical, legally-sourced data collection with zero PII ingestion and horizontal scalability

Interested in Learning More?

Check out the source code or see the project in action

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