If you're still piecing together single-purpose CLI utilities for digital footprinting, your setup is holding you back.
Running Sherlock gives you raw social media links. Running Holehe tells you if an email exists on dead endpoints. Running Maigret dumps massive, unfiltered noise across thousands of unverified checks. None of them connect the dots automatically—leaving you to manually copy handles, extract bio links, and guess whether two profiles belong to the same person.
user-scanner changes the game entirely. It is the first unified 2-in-1 OSINT suite designed to pivot a single email or handle into masked phone numbers, locations, breach intel, and a fully scored identity graph.
⚡ The Ultimate Recon Showdown: Sherlock vs. Maigret vs. user-scanner
| Feature | 🐢 Sherlock | 🌀 Maigret | 🚀 user-scanner
|
|---|---|---|---|
| Target Vectors | Username Only | Username Focus | 2-in-1 (Email + Username) |
| Pivoting Engine | ❌ None | Basic/Manual | --cross-scan Multi-Pass Recursion |
| Masked Phone & PII Mining | ❌ | ❌ | ✅ Extracts Masked Phones, Bios & Locations |
| Maintainability & Updates | Slow / Decaying | Massive / High False Positives | ✅ Smart Auto-Update Prompts via PyPI |
| Infostealer Breach Intel | ❌ | ❌ | ✅ Integrated Hudson Rock (--hudson) |
| Evasion & Concurrency | Basic requests
|
High Request Overhead | curl_cffi Browser TLS Impersonation |
| Confidence Scoring | ❌ | Basic | ✅ Automated Anchoring (confirmed, likely) |
🎯 How user-scanner Turns 1 Email into a Full Identity Profile
1. The Power of --cross-scan (Unlocking Masked Phones & Locations)
An email check proves registration, but it rarely shows the user's name. A username scan hits hundreds of social platforms, but requires a target handle to start.
--cross-scan bridges the two automatically:
# Start with a single email address
user-scanner -e target@example.com --cross-scan
# Pass 1 (Email Vector):
# Hits account recovery and profile lookup endpoints
# (e.g., Gravatar, Google, Samsung, PayPal).
# PII & Handle Mining:
# Extracts published handles, bio text, locations, and
# masked phone numbers exposed by security recovery hints.
# Pass 2 (Username Sweep):
# Automatically feeds mined handles back into username
# modules to find matching social profiles, GitHub repos,
# and developer accounts.
# Pass 3 (Location & Bio Aggregation):
# Aggregates explicit location strings from discovered
# profiles to build the target's public footprint.
2. Smart Auto-Update System (Always Up-To-Date)
Web platforms alter their authentication flows and DOM structures constantly—making static tools break within weeks.
user-scanner includes a Smart Auto-Update System that checks PyPI signatures on execution and prompts you for seamless, interactive updates. Your modules and detection vectors stay fresh without manual git pull maintenance.
3. High-Throughput Engine with TLS Impersonation
Modern platforms instantly block generic Python requests with Cloudflare 403 responses. user-scanner uses curl_cffi to mimic real browser JA3/JA4 TLS fingerprints while using httpx for high concurrency.
🛠️ Quickstart Guide
Installation via PyPI
pip install user-scanner
Or run instantly via Nix without installing:
nix run github:kaifcodec/user-scanner/main -- --help
Essential Workflow Commands
# 1. Single Email Scan with Hudson Rock Breach Intel
user-scanner -e target@example.com --hudson
# 2. High-Precision Link Graph Walk
# Zero Guessing / No False Positives
user-scanner -u target_handle --cross-scan --cross-sweep 0 --cross-depth 2
# 3. Export Complete OSINT Report with Scraped Avatars
user-scanner -u target_handle -f pdf -o target_report.pdf
🏆 The Verdict
- Sherlock is too basic for modern OSINT.
- Holehe is unmaintained and unravelling.
- Maigret generates overwhelming noise and lacks cross-vector logic.
user-scanner is the clear winner—the all-in-one OSINT tool designed to turn a single input into a connected, confidence-scored identity graph.
- GitHub Repository: kaifcodec/user-scanner
- PyPI Package: pypi.org/project/user-scanner
