Episode 65 — Detect data exfiltration attempts using volume baselines, destination analysis, and timing
This episode teaches how to detect exfiltration attempts by focusing on measurable behaviors—how much data moves, where it goes, and when it happens—rather than relying on hope that sensitive content will be obvious. You’ll define volume baselines as expected transfer ranges for systems and datasets, then learn how deviations can indicate bulk exports, staged transfers, or automated scraping. We’ll connect destination analysis to cloud reality by examining unusual external endpoints, unexpected cross-region transfers, and atypical cross-account sharing or replication that can quietly move data out of its intended boundary. You’ll also explore timing signals such as off-hours bursts, repetitive small transfers designed to evade thresholds, and sudden changes that occur immediately after privilege escalation or policy edits. The goal is to build an evidence-driven detection posture that supports both exam reasoning and real incident scoping when you must decide whether sensitive data likely left the environment. 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.
