Episode 36 — Encrypt AI Data Correctly: In Transit, At Rest, and In Use
This episode focuses on encryption as a foundational control that SecAI+ expects you to apply with precision, because AI pipelines often move data across ingestion services, storage layers, training infrastructure, and inference endpoints, and every handoff is an exposure opportunity. You will learn what “in transit” means in practical terms, how to ensure strong transport protections between internal services, and how certificate and key management failures can undermine encryption even when protocols look correct on paper. We will cover “at rest” encryption across object storage, databases, vector stores, and backups, emphasizing how access control and key separation determine whether encryption actually reduces breach impact. You will also learn what people usually mean by “in use” protections, why it is harder than the other two categories, and how to think about realistic safeguards such as trusted execution environments, secure enclaves, or strict isolation when handling sensitive workloads. Troubleshooting considerations include diagnosing misconfigured TLS, avoiding accidental plaintext logs, validating key rotation practices, and ensuring encryption decisions align with data classification and regulatory expectations rather than being applied inconsistently. 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.
