User Scanner
User Scanner: quickstart de una comprobación OSINT acotada
Módulos email/username, profundidad cross-scan, exportación y verificación defensiva.
Qué aprenderás
- Explain module, pivot, report, and MCP layers
- Run a bounded scan and interpret uncertainty
- Apply authorization, rate-limit, and data-retention controls
Antes de empezar
- Basic Git and command-line usage
- Comfort reading a project README
You can explain the project, run its documented first step, and decide what to verify before adopting it.
Conclusiones clave
- Begin with an owned/synthetic identity and one module.
- Keep cross-scan depth, concurrency, proxies, and collected fields bounded.
- Treat hits as leads requiring human verification and controlled retention.
Use an owned or synthetic identity
Empieza con una identidad propia o sintética y un módulo, añade cross-scan de baja profundidad solo con autorización y exporta JSON para revisión humana. Un hit no prueba identidad.
Install in a virtual environment, pin the package/repository version, and record the target type, timestamp, modules, proxy policy, and output path in a run card.
Choose one module before a full scan
Use `-m github` or a category flag to validate one module, then expand only when the result is useful. Compare username (`-u`) and email (`-e`) behavior, and export JSON for review before producing a PDF or CSV handoff.
A positive result is a lead, not identity proof. Check response age, profile URL, UID or other metadata, and independently verify before writing a finding.
Add pivots deliberately
`--cross-scan` mines handles, profile links, or public emails and can recurse with `--cross-depth`. Keep depth low, prefer verified links, bound concurrency, and record every pivot edge so a reviewer can see why a secondary target was queried.
Proxy rotation and TLS impersonation may improve reachability but also increase rate-limit and terms-of-service risk. Use only permitted networks and do not bypass access controls.
Review and clean up
Inspect JSON, then generate PDF/CSV only for the fields the investigation needs. Redact or delete unnecessary avatars, bios, follower counts, and exposed addresses; encrypt retained reports and assign a reviewer.
Cómo elegir
| Criterio | Opción A | Opción B |
|---|---|---|
| Best when | You need predictable behavior and easy auditing | You need adaptive optimization and have reliable telemetry |
| Main risk | May leave performance on the table | Can become difficult to explain or debug |
Pasos de implementación
- 1
Install in a pinned virtual environment and define scope.
- 2
Run one username/email module and export JSON.
- 3
Add a low-depth verified cross-scan only when authorized.
- 4
Review, redact, encrypt, and delete outputs according to policy.
Ejemplo para copiar
python3 -m venv .venv
. .venv/bin/activate
pip install user-scanner
user-scanner -u owned-handle -m github -f json -o results.json
user-scanner -u owned-handle --cross-scan --cross-links verified --cross-depth 1Preguntas frecuentes
Should I run all 465+ vectors immediately?
No. Start with one authorized module and expand only for a documented purpose.
What does cross-scan prove?
It finds candidate pivots from public responses; each edge still needs verification and lawful handling.
Fuentes
- User Scanner README (captured 2026-08-31)Fuente verificada 2026-08-31
- User Scanner repositoryFuente verificada 2026-08-31