phishing detection

A hands-on guide to building an AI-assisted phishing detection pipeline you can run entirely from a Linux terminal: aggregate OpenPhish/URLHaus feeds, score URLs with a lightweight Python ML helper, validate DKIM/DMARC, and scan attachments with ClamAV/YARA. Includes copy-paste installs, ready-to-use Bash/Python scripts, tuning tips, and automation for a local, modular, privacy-preserving defense.

Guide for web developers and sysadmins to bolster security by combining Bash automation with AI for real-time phishing detection. Covers prerequisites, environment setup with Python/TensorFlow, using pre-trained models or APIs (PhishTank, Google Safe Browsing), Bash–Python integration, cron-based monitoring and logging, and best practices on privacy, updates, and reducing false positives within a layered defense.