Episode 9 — Risk, Likelihood, and Impact in Practice
This episode translates risk math into plain language you can apply under time pressure. We clarify how likelihood describes the chance a scenario materializes within a defined period, while impact captures the consequence if it does—and why both are context-dependent. You’ll hear when qualitative scales are sufficient, when semi-quantitative scoring helps, and how to avoid common pitfalls like multiplying ordinal values or averaging away tail risk. We also cover how controls influence likelihood versus impact differently, and how residual risk should be stated after mitigations are in place.
To ground it, we work through example scenarios—ransomware against remote desktops, data exfiltration via misconfigured cloud storage, or credential stuffing on a customer portal—and demonstrate fast, defensible reasoning: what indicators change likelihood today, what dependencies amplify impact, and which mitigations flip the decision. The episode equips you with exam-ready phrasing, simple calibration tricks for scoring, and decision frames you can apply in governance meetings without resorting to hand-waving. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
