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performing-ai-driven-osint-correlation

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Use AI/LLM-based reasoning with Sherlock, theHarvester, and SpiderFoot to correlate OSINT findings—usernames, emails, social profiles, domain records, breach databases, and dark-web mentions—into unified, confidence-scored intelligence profiles with link analysis. Use when raw OSINT data from multiple sources needs merging into one target profile or resolving identity linkage across platforms.

skills/performing-ai-driven-osint-correlation/SKILL.md

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# Performing AI-Driven OSINT Correlation

## When to Use

- You have collected raw OSINT data from multiple tools and sources but need to identify connections, contradictions, and patterns across them.
- You need to build a unified intelligence profile for a target entity (person, organization, or infrastructure) from fragmented data.
- Traditional manual correlation is too slow or error-prone for the volume of data collected.
- You want confidence-scored assessments of identity linkage across platforms rather than simple keyword matching.

## Prerequisites

- Python 3.10+ with `requests`, `json`, and `csv` libraries
- [Sherlock](https://github.com/sherlock-project/sherlock) installed (`pip install sherlock-project`)
- [theHarvester](https://github.com/laramies/theHarvester) installed (`pip install theHarvester`)
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