Filling the Gap in Risk Management: Probabilistic Threat Modeling

This article explains how to apply probabilistic threat modeling to cyber risk management by treating attack chains (e.g., phishing, malvertising, credential leaks, brute force) as Markov chains and quantifying likelihood using control effectiveness and event frequency. Through a hypothetical company protecting source code, it derives success probabilities for multiple vectors, converts them into annualized likelihoods, and shows how changes like team growth or increased phishing/malware activity affect overall risk exposure and guide control investment decisions.