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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✨ 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.

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🚀 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