Overview
Relevant source files
This page provides a comprehensive overview of the Sherlock Project, an OSINT (Open Source Intelligence) tool designed to hunt down social media accounts by username across 400+ social networks. For detailed information about installation methods, see Installation and Usage, and for contribution guidelines, see Contributing.
What is Sherlock?
Sherlock is a command-line tool that allows users to search for specific usernames across hundreds of social networks simultaneously. The project is designed to help with reconnaissance and information gathering by checking if a given username exists on various platforms.
Sources: pyproject.toml10-14 docs/README.md4-6
Key Features
- Search for usernames across 400+ social networks
- Multiple output formats (text, CSV, Excel)
- Proxy and Tor support for anonymous searching
- Asynchronous processing for improved performance
- Detailed error detection to accurately determine account existence
- Docker deployment option for containerized operation
Sources: docs/README.md54-99 pyproject.toml42-52
System Architecture
Sherlock follows a data-driven architecture where the core engine processes usernames against a rich database of site configurations to determine account existence.
Sources: pyproject.toml61 Dockerfile31
Username Search Process
The core functionality of Sherlock revolves around the username search process, which follows a systematic approach to checking usernames across various social networks:
Sources: docs/README.md40-51
Error Detection Methods
Sherlock employs sophisticated error detection mechanisms to accurately determine if a username exists on a particular platform:
Deployment Options
Sherlock can be deployed through multiple methods:
| Deployment Method | Command | Notes |
|---|---|---|
| Python Package | pipx install sherlock-project | Recommended for most users |
| Docker | docker run -it --rm sherlock/sherlock | Containerized deployment |
| Package Managers | dnf install sherlock-project | Available for some Linux distributions |
Additional community-maintained packages are available for Debian, Ubuntu, Homebrew, Kali, and BlackArch.
Sources: docs/README.md29-36 Dockerfile27
Project Organization
The Sherlock project is organized with a focus on maintainability and extensibility:
Sources: pyproject.toml9-37 Dockerfile15-25
Command Line Interface
Sherlock provides a comprehensive command-line interface with numerous options for customizing searches:
sherlock username [options]
Key options include:
- Output formatting (
--csv,--xlsx) - Network options (
--tor,--proxy) - Site filtering (
--site SITE_NAME) - Result control (
--print-found,--print-all)
For a complete list of options, see Command Line Interface.
Sources: docs/README.md54-99
Project History and Maintenance
Sherlock was originally created by Siddharth Dushantha and is now maintained by a team of contributors:
- Paul Pfeister
- Matheus Felipe
- Sondre Karlsen Dyrnes
The project continues to evolve with regular updates to the site database and functionality improvements.
Sources: pyproject.toml15-21 docs/README.md120-121
Technical Requirements
Sherlock requires:
- Python 3.9 or newer
- Several dependencies, including requests, colorama, and PySocks
- Optional Tor integration for anonymous searching
Sources: pyproject.toml43-52
Conclusion
Sherlock is a powerful OSINT tool for username reconnaissance across social networks. Its data-driven architecture allows for easy expansion to new platforms, while its flexible error detection methods accommodate different website implementations. With multiple deployment options and comprehensive documentation, Sherlock provides an accessible and effective solution for social media account discovery.
For more detailed information about the core architecture and components, see Core Architecture.