Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI and machine learning are already being used in cybersecurity to help reduce the "noise of all the indicators" that security teams receive. These systems can serve as a "first line of defense" by setting up potential response actions. However, organizations need to ensure they keep human analysts in the loop because contextual knowledge and human judgment remain critical. Data Security Decoded is available on our YouTube channel!

In this episode of Data Security Decoded, host Caleb Tolin sits down with Kyle Fiehler, Sr. Transformation Analyst at Rubrik Zero Labs, to explore why backup data has become a critical — and largely ignored — form of security telemetry.

In this episode of Building Cyber Resilience: A Healthcare Leader’s Guide, host Josh Howell speaks with Errol Weiss, Chief Security Officer at Health-ISAC. Drawing on decades of experience across government, finance, and healthcare, Errol walks through what leaders actually face in the hours and weeks following a cyberattack. The conversation explores why healthcare remains a top ransomware target, how uncertainty shapes recovery decisions, and why trusted, anonymous information sharing has become one of the sector’s strongest defenses.

Everyone knows ChatGPT, but Agentic AI is where the real work happens. In this Agentic AI vs GenAI breakdown, we explain why Agentic AI is the next major leap, and what it means for your business and career. Here’s the difference: Generative AI (GenAI): Creates content. You ask, it writes, summarizes, or creates. Agentic AI: Does work. It is built on three core components: a brain (reasons), memory (context), and tools (the key that lets agents touch real systems like APIs and databases).