go-osint

A lightweight, efficient OSINT tool built in Go for username and keyword searches across multiple platforms. Inspired by Sherlock but optimized for simplicity and speed using Go routines.

🌟 Features

• Username Search: Find digital footprints across various platforms
• Keyword Discovery: Uncover URLs related to specific search terms
• Domain Search: Identify platforms associated with a domain
• Concurrent Processing: Leverages Go routines for fast, efficient searches
• File Output: Save search results for later analysis
• Platform Specific: Option to target searches to individual platforms

🚀 Quick Start

1. Clone and build:

git clone https://github.com/vehbiu/go-osint.git
cd go-osint
go build

2. Run a search:

go-osint username johndoe

🛠️ Usage Examples

📋 Command Structure

go-osint [type] [term] (platform)

🔍 Search Types

1. All-Platform Username Search:

   go-osint username johndoe

2. Platform-Specific Search:

   go-osint username johndoe github

3. Keyword Search:

   go-osint keywords johndoe.22

4. Domain Search:

    go-osint domain example.com

5. Save Results to File:

   go-osint username johndoe --output results.txt

📁 Project Structure

go-osint/
├── main.go           # Entry point
├── username/         # Username-specific search functions
├── keywords/         # Keyword-specific search functions, (currently only google seearches)
├── domain/           # Domain-specific search functions
└── README.md         # Documentation

⚙️ Technical Details

• Built in Go for maximum efficiency
• Uses Go routines for concurrent searches
• Platform-specific functions for unique handling

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Feel free to:

• Open issues
• Submit pull requests
• Suggest new platforms to add

👤 Author

Vehbi

• GitHub: @vehbiu

🔒 Responsible Use

This tool is for educational purposes only. Users are responsible for ensuring their usage complies with applicable laws and respects privacy.

🙏 Acknowledgments

• Inspired by Sherlock

📊 Stats

💭 Developer's Note

While this project shares similarities with Sherlock, it's different. Rather than copying sherlock, the methods are implemented manually (which can be seen from the abstraction), although not the greatest, it works for such a project.

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Made with ❤️ by @vehbiu