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osint-recon

Automate open-source intelligence collection and structured reconnaissance for usernames, domains, emails, and organizations.

6|1|Updated Apr 7, 2026
Search Tags:#reconnaissance#osint#threat-intelligence#social-media-analysis#domain-intel#username-enumeration#dark-web
One-click install
npx skills add https://github.com/kmshihab7878/claude-code-setup --skill osint-recon-kmshihab7878
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: osint-recon
Source: https://github.com/kmshihab7878/claude-code-setup/tree/main/skills/osint-recon
Command: npx skills add https://github.com/kmshihab7878/claude-code-setup --skill osint-recon-kmshihab7878

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provide a repeatable, ethical methodology to collect, normalize, and correlate open-source intelligence for targets such as usernames, domains, emails, and organizations so investigators can produce defensible findings without ad-hoc workflows.

Core Features & Use Cases

  • Username and profile enumeration: Multi-platform checks and cross-platform correlation to locate user identities and associated accounts.
  • Domain and infrastructure intelligence: DNS, WHOIS, certificate transparency, and subdomain discovery to map attack surface and ownership.
  • Email and breach assessment: Verify MX/SPF/DMARC records, check breach exposures, and infer organizational address patterns.
  • Dark web and CTI aggregation: Aggregate feeds, classify indicators with confidence levels, and prioritize threat indicators.
  • Integration and auditing: Store entities in a memory MCP graph, log actions to audit trails, and follow legal and rate-limit safeguards.
  • Use Case: Run a targeted investigation to enumerate a suspicious username across platforms, gather linked domains and email variants, and export a confidence-scored findings table for a security report.

Quick Start

Use the osint-recon skill to enumerate usernames, gather domain and email evidence for target example.com, and return a confidence-scored findings summary.

Frequently Asked Questions about osint-recon

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I collect open-source intelligence for a target username across multiple platforms?▼

Open-source intelligence collection for a target username is automated through multi-platform checks and cross-platform correlation to locate user identities and associated accounts, returning normalized findings with classified confidence levels.

What is the best way to map a domain's attack surface and infrastructure ownership?▼

Domain infrastructure intelligence is gathered by checking DNS, WHOIS, certificate transparency logs, and performing subdomain discovery to map the attack surface and identify ownership details for the target domain.

How does structured reconnaissance handle dark web monitoring and threat intelligence aggregation?▼

Structured reconnaissance aggregates dark web and threat intelligence feeds, classifies indicators with confidence levels, and prioritizes threat indicators to produce a defensible findings summary for security investigations.

Do I need to configure memory MCP stores to store and audit OSINT entities?▼

Memory MCP graph integration is supported to store collected entities and log actions to audit trails. This integration normalizes evidence and maintains a repeatable, defensible methodology for security investigations.

What legal and ethical constraints apply to automated OSINT investigations?▼

Automated OSINT investigations satisfy legal and ethical constraints by adhering to robots.txt rules and enforcing rate limits during data collection, ensuring reconnaissance remains within defensible boundaries and avoids prohibited scraping.

Can I verify email breach exposures and organizational address patterns during reconnaissance?▼

Email and breach assessment verifies MX, SPF, and DMARC records, checks breach exposures, and infers organizational address patterns to correlate evidence and produce confidence-scored findings for the investigation report.

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