How do web attackers exploit applications for financial gain through credential resale, money laundering, headless browser automation, and MFA-bypassing phishing proxies, and why does cyber fraud remain low-risk yet highly profitable? 📕This article forms part of the notes from Week 1 of the Data Science for Security and Fraud online

How do web applications work? What are the key concepts that you should know, and some tools for automating web requests? 📕This article forms part of the notes from Week 1 of the Data Science for Security and Fraud online course. Access the full course outline here. We’ve grown so

Learn how to use browser dev tools and Postman to analyze web traffic. 📕This article forms part of the notes from Week 1 of the Data Science for Security and Fraud online course. Access the full course outline here. In this video, you will learn how to use Developer Tools

🧰This article is the project for Week 1 of the Data Science for Security and Fraud online course. Access the full course outline here. You are trying to join The Shadows, a shadowy international gang that is rumored to be the world’s most profitable crime syndicate. Its members and methods

Learn how to effectively analyze and clean web application data, ensure consistency across logs, enrich the dataset with additional information, explore traffic patterns, identify anomalies, and build accurate models for fraud detection. 📕This article forms part of the notes from Week 2 of the Data Science for Security and Fraud

How can we differentiate bot from human traffic? What are some typical features? 📕This article forms part of the notes from Week 2 of the Data Science for Security and Fraud online course. Access the full course outline here. How to identify (bad) bot traffic? It is always possible to