performing-ai-driven-osint-correlation - Correlate Multi-Source OSINT into Entity Profiles
Uses Sherlock, theHarvester, SpiderFoot, and an LLM to normalize OSINT findings, correlate identities, score link confidence, and generate intelligence profiles.
Tags
Updated: 2026-09-28Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Collect multi-source OSINT findings
- Normalize findings into a common schema
- Correlate identities across sources
- Score identity link confidence
- Resolve and merge related identities
- Generate intelligence profile reports
Inputs
- Target usernames, domains, or email addresses
- Raw OSINT results
- Breach database API keys
- LLM API access
Outputs
- Sherlock result files
- theHarvester result files
- SpiderFoot result files
- Normalized findings JSON
- Correlation report JSON
- Intelligence profile Markdown
- Confidence-scored entity links
Requirements
- Python 3.10+
- Python requests, json, and csv libraries
- Sherlock installed
- theHarvester installed
- SpiderFoot 4.0+ on localhost:5001
- LLM API access
- Optional Maltego CE
- Optional external service API keys