The Professional OSINT & Digital Intelligence Framework
- 🌟 Overview
- 🔥 Why HawkLens?
- 🚀 Key Features
- 🛠️ Architecture
- 🏁 Getting Started
- 📡 API & Integration
- 📂 Documentation
- 🤝 Contributing
- 📄 License
HawkLens is a high-performance, modular OSINT (Open Source Intelligence) framework engineered in Golang. Designed for intelligence analysts and researchers, it provides a centralized platform to concurrently collect, analyze, and visualize digital footprints across major social media landscapes.
By combining an interface-driven plugin architecture with a robust worker pool and real-time streaming capabilities (SSE), HawkLens transforms raw data into actionable intelligence with unmatched velocity.
In the fast-paced world of digital intelligence, speed and modularity are non-negotiable.
- Unmatched Speed: Built with Go routines and a managed dispatcher, scanning 5+ platforms takes milliseconds.
- Production Ready: Fully containerized stack for seamless deployment and scalability.
- Deep Insights: Beyond collection, HawkLens performs on-the-fly Sentiment Analysis and Topic Modeling.
- Modern UX: A premium dashboard focused on clarity, responsiveness, and data storytelling.
| Feature | Description |
|---|---|
| Managed Engine | A sophisticated Worker Pool Dispatcher for balanced resource consumption. |
| Real-time SSE | Live-streaming results from backend to frontend without page refreshes. |
| Modular Plugins | Support for Twitter (X), YouTube, Reddit, Instagram, and TikTok through a uniform interface. |
| NLP Pipeline | Built-in sentiment grading and automated topic categorization. |
| Storage & Search | Hybrid persistence using PostgreSQL for data and Elasticsearch for full-text search. |
| Flexible CLI | A feature-rich command line interface with beautiful tables and progress indicators. |
HawkLens follows a decoupled, micro-service ready architecture:
- Core Engine: Orchestrates the scan lifecycle and handles concurrency.
- Plugin Layer: Abstracted data collectors that implement the
Plugininterface. - Persistence Layer: Structured storage (PostgreSQL) and search indexing (Elasticsearch).
- Communication: REST API for management and SSE for real-time telemetry.
Tip
Check out the Architecture Deep Dive for a detailed technical breakdown and Mermaid diagrams.
The easiest way to experience HawkLens is via Docker Compose.
# Clone the repository
git clone https://github.com/ismailtsdln/HawkLens.git
cd HawkLens
# Start the intelligence stack
docker-compose up --buildAccess the dashboard at http://localhost:8080.
# Compile the framework
go build -o hawklens cmd/hawklens/main.go
# Execute a multi-platform scan
./hawklens scan "cybersecurity" \
--format json \
--output report.json \
--db # Save to persistenceHawkLens is designed to be integrated into larger ecosystems.
GET /api/v1/scan-stream?query=intelligence
Content-Type: text/event-streamExplore the API Documentation for full endpoint specifications.
Detailed technical documentation is available in the docs/ directory:
We welcome contributions from the community! Whether it's a new platform plugin, a bug fix, or a UI enhancement, your input is valuable.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Built for Intelligence. Designed for Speed. 🦅