Darktrace SDK with full Endpoint/Parameter support. Easy install via pip

A modular data governance suite that transforms regulatory case files into structured intelligence. It models breach taxonomies, remediation actions, platform risk surfaces, credential hygiene failures, vendor accountability chains, response lag timelines, and cross-jurisdictional enforcement trends. Powered by PDPC data and AI.

This project investigates native Windows Security log data using Splunk to simulate real-world threat detection practices in a SOC (Security Operations Center) environment. The objective is to identify and understand system activity patterns, detect suspicious behaviors, and apply basic detection logic using SPL (Search Processing Language).

Curated portfolio of reproducible data-science playbooks across marketing, cybersecurity, NLP, finance, HR, energy, and startup analytics.

Purpose: analyze Windows Security Logs using Splunk to develop a behavioral baseline and investigate host activity patterns.

This project uses Machine Learning and NLP to detect phishing websites based on URL patterns. Built with Python, it applies data preprocessing, feature extraction, and classification using Logistic Regression and Naive Bayes—achieving over 96% accuracy.