Description

Description
This proposal introduces a new module to Sherlock for evaluating the authenticity and risk level of discovered accounts using multimodal AI (image + text analysis). While Sherlock excels at detecting username presence, it currently lacks risk scoring or bot/impostor detection. By combining screenshots, profile metadata, and deep learning, I aim to transform Sherlock into a more intelligent OSINT tool for cybersecurity professionals.

Integration:

Add a CLI flag (e.g., --risk) to trigger this module.

Include risk data in the output file (JSON/CSV).

Optionally visualize results in a UI/dashboard for review and export.

Impact:

Speeds up manual OSINT review by pre-filtering suspicious accounts.

Enhances threat intelligence and bot/phishing detection.

Helps investigators prioritize targets and automate triage.

Request:
I would like to further explore and prototype this feature, possibly as an optional extension or module. Please let me know if this direction aligns with the project's vision, and whether a formal design or Pull Request would be welcomed.

Code of Conduct

• I agree to follow this project's Code of Conduct