kaifcodec/user-scanner

User Scanner

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A powerful 2-in-1 OSINT suite engineered for deep Email and Username Intelligence.

With 2720+ total scan vectors—including 210+ email-integrated sites and 2510+ username platforms—you can map digital footprints, analyze target behavior, uncover interests, full metadata of usernames and verify account registrations in seconds.

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💖 Sponsored by

Go beyond account enumeration. WebVetted turns an email or username into a complete identity investigation with deep OSINT enrichment, breach intel, AI analysis, and an interactive identity graph.
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Comprehensive OSINT platform for professional investigators and analysts. Reverse email, phone number, and username search across 250+ modules. Automate your intelligence gathering with our powerful tools.
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Find beginner-friendly open-source issues and make your first pull request today.
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🔍 Looking for Phone Number OSINT? Check out our other project phonsint to uncover accounts, masked emails, and profile photos with zero SMS alerts. Explore phonsint →

✨ Key Features

• 🔎 Deep Email & Username OSINT: Look up email registrations and perform advanced username profiling across 2710+ platforms.
• 👤 Rich Metadata Scraping: Scrapes avatars, bio descriptions, follower counts, UID numbers, seller statuses, and account attributes.
• 🔀 Cross-Scan & Pivot Engine: Mines handles, profile links, and exposed email addresses from initial scans, automatically pivoting across secondary target vectors.
• 🤖 Model Context Protocol (MCP) Server: Native AI agent integration for Claude Desktop, Cursor, Antigravity, and LLMs to run autonomous OSINT scans and recursive pivots.
• 🛡️ Hudson Rock Infostealer Breach Intel: Query infostealer malware breach logs using the --hudson flag for high-priority target correlation.
• ⚡ High-Throughput Parallel Engine: Powered by httpx and curl_cffi for maximum concurrency with automated TLS fingerprint impersonation.
• 🔀 Permutation & Alias Generator: Wildcard-based username variation generation to catch typosquatting or alternative aliases.
• 📂 Multi-Format Reports: Automated exports to PDF (with profile photos), JSON, and CSV for pipeline integration.
• 🌐 Advanced Proxy Pivoting: Built-in proxy rotation with protocol auto-detection (http, socks5) and pre-scan health validation (--validate-proxies).
• 🎨 Responsive Terminal UI: Dynamic progress tracking, self-adaptive category grids (-lu/-le), and clear status reporting.

🚀 Installation

🐍 Via PyPI (Recommended)

# Upgrade pip and install user-scanner
python3 -m pip install --upgrade pip
pip install user-scanner
Optional: Install with MCP Server support for AI agents
pip install "user-scanner[mcp]"

📦 Virtual Environment Setup

# Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\Activate.ps1
Install package
pip install user-scanner

❄️ Via Nix (Linux & macOS)

# Run instantly without installing permanently
nix run github:kaifcodec/user-scanner/main -- --help
Drop into a temporary shell with user-scanner active
nix shell github:kaifcodec/user-scanner/main

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💻 Usage Guide

1. Basic Username & Email Scanning

Scan a single username or email address across all available platform modules:

user-scanner -u johndoe             # Single username scan
user-scanner -e [email protected]   # Single email scan
user-scanner -u johndoe --email-domains global  # Try johndoe across provider domains

2. Cross-Scan & Pivot Intelligence

An email scan proves an account exists but rarely reveals a handle. --cross-scan mines exposed handles, profile links, and secondary email addresses from target profiles, pivoting into multi-pass reconnaissance across all matching platforms:

| Pivot Direction | What it Mines | | :--- | :--- | | -e → username | Handles or social links exposed on an email's registered profile | | -u → username | Secondary aliases advertised across target social profiles | | -u → email | Public email addresses published on target profile pages | | -e → email | Secondary addresses exposed by initial email profiles |

user-scanner -u johndoe --cross-scan                                  # Pivot from username scan
user-scanner -e [email protected] --cross-scan                        # Pivot from email scan
user-scanner -e [email protected] --cross-scan --cross-links verified # Platform-verified links only
user-scanner -u johndoe --cross-scan --cross-depth 2        # Follow links two hops deep

💡 For confidence scoring, link classification rules, and cost models, see docs/CROSS_SCAN.md.

3. Hudson Rock Malware Breach Intelligence

Check if a target username or email address has been exposed in infostealer malware infection logs:

user-scanner -u johndoe --hudson             # Username malware log check
user-scanner -e [email protected] --hudson   # Email malware log check

🖼️ To view output terminal screenshots and visual previews, see docs/EXAMPLES.md.

4. Targeted Category & Module Scanning

Scan specific categories or individual modules, or list available modules in a responsive grid:

user-scanner -u johndoe -c dev                # Developer platforms only
user-scanner -e [email protected] -m github   # Single module check
user-scanner -u johndoe -m github,instagram   # Specific comma-separated modules
user-scanner -lu                              # List user categories & modules grid
user-scanner -le                              # List email categories & modules grid

5. Bulk File Scanning

Scan multiple targets from an input file (one target per line):

user-scanner -uf usernames.txt   # Bulk username scan
user-scanner -ef emails.txt      # Bulk email scan

6. Report Exports, Options & Proxies

# Export results to PDF, JSON, or CSV
user-scanner -u johndoe -f pdf -o report.pdf
user-scanner -u johndoe -f json -o results.json
Verbose URL reporting and show all results (including not found)
user-scanner -u johndoe -v --all
Rotate proxies with pre-scan validation check
user-scanner -u johndoe -P proxies.txt --validate-proxies

7. AI & LLM Agent Integration (MCP Server)

Connect user-scanner directly to AI coding assistants and LLM platforms via the Model Context Protocol (MCP). This enables AI agents (Claude Desktop, Cursor, Antigravity, Open-WebUI) to autonomously investigate handles and emails, pivot on exposed profiles, and analyze digital footprints.

Starting the Server

# Start the MCP server over standard I/O (stdio)
user-scanner-mcp
Optional: Enable verbose logging to stderr
user-scanner-mcp -v

MCP Client Configuration

Add user-scanner to your client configuration (e.g. claude_desktop_config.json or mcp_config.json):

{
  "mcpServers": {
    "user-scanner": {
      "command": "user-scanner-mcp"
    }
  }
}

Exposed AI Tools

| Tool | Description | Capabilities | | :--- | :--- | :--- | | scan_username | Deep username OSINT & profile enrichment across platforms | Targeted scans (category, module), recursive cross_scan, proxy injection, loudness toggles | | scan_email | Deep email verification & account discovery across platforms | Target scoping, automated link pivoting (cross_scan), custom proxies, loudness toggles | | list_available_modules | Dynamic catalog & module discovery | Allows AI agents to query all supported platforms and categories dynamically |

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📚 Documentation Hub

Explore detailed documentation guides in the docs/ directory:

• 📋 CLI Flags Reference — Complete breakdown of every CLI flag and option.
• 🔀 Cross-Scan & Pivoting Guide — In-depth guide to multi-pass cross-scan reconnaissance.
• 🔀 Pattern Syntax Guide — Wildcard and permutation patterns for username generation.
• 🐍 Library Mode Guide — Calling the Python engine programmatically from your own scripts.
• 🌐 Proxy & Network Guide — Proxy rotation formats, health checks, and regional VPN troubleshooting.
• 🖼️ Media & Output Gallery — Video demonstrations, terminal recordings, and screenshot previews.

🐍 Python Library Mode

Integrate the User Scanner engine directly into your Python scripts:

import asyncio
from user_scanner.core import engine
from user_scanner.email_scan.shopping import etsy
async def main():
    # Engine validates target against module and returns Result object
    result = await engine.check(etsy, "[email protected]")
    print(result.to_json())
asyncio.run(main())

💡 For complete Python API documentation and batch category checking examples, see docs/USAGE.md.

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💖 Support the Project

Web platforms constantly update authentication flows. Maintaining over 2710+ scan modules requires around-the-clock commitment to keep the suite reliable and free for the cybersecurity community.

If user-scanner has saved you hours of manual pivoting or aided your investigations, consider supporting the project:

👉 Sponsor on GitHub

Project Sponsors

Huge thanks to our amazing sponsors who support the ongoing development of user-scanner!

@soxoj

@hienyimba

@InDieTasten

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📜 Contributing

We welcome community contributions! Please read our Contributing Guidelines before opening a PR or submitting new scan modules.

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⚠️ Disclaimer

This tool is provided strictly for educational purposes, authorized security research, and defensive OSINT investigations. The developers assume no liability and are not responsible for any misuse, unintended consequences, or legal actions resulting from the deployment of this software.