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Data Security DecodedWelcome to the Data Security Decoded podcast your guide to navigating the complex world of data protection. Each episode breaks down key cybersecurity issues and cyber resilience strategies in clear, accessible language. We speak with business leaders and cybersecurity experts to keep you informed about the latest trends and help you future-proof your data security. Join us on this essential journey. Author: Rubrik
Data Security Decoded provides actionable, vendor-agnostic insights to reduce data security risk and improve resilience outcomes. Designed for cybersecurity and IT professionals who want practical insights on preparing for attacks before they happen, so they can respond effectively when they inevitably do. Episodes feature insights from researchers, crafters of public policy, and senior cybersecurity leaders, to help organizations reduce risk and improve resilience. Data Security Decoded provides practical advice, proven strategies, and in-depth discussions on the latest trends and challenges in data security, helping listeners strengthen their organizations' defenses and recovery plans. Language: en-us Genres: News, Tech News, Technology Contact email: Get it Feed URL: Get it iTunes ID: Get it |
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The Three-Layer Strategy for Autonomous Agent Governance with Joe Hladik and Amit Malik
Episode 51
Tuesday, 21 April, 2026
The race for AI dominance has created a dangerous imbalance between business velocity and cyber resilience. In this episode, host Caleb Tolin is joined by Joe Hladik, Head of Rubrik Zero Labs, and Staff Security Researcher Amit Malik to break down the findings of their latest report on agentic adoption. The discussion centers on the Agentic Paradox. This is the technical reality that tools designed to automate high-level tasks are inherently built to find the most efficient path around obstacles, including existing security policies. A primary focus is implementing a three-layer framework for AI Operations. This model targets the Tool Layer, where agents interact with databases; the Cognitive Layer, which serves as the LLM brain; and the critical Identity Layer. The conversation explores stories in which agents, without malicious intent, have caused catastrophic data loss simply by following an optimized logic path. These instances prove that agents need not be sentient to be destructive when they lack proper human-in-the-loop checkpoints. Technical hurdles of Identity Resilience are also addressed, specifically the explosion of non-human identities that spin up and down like elastic cloud infrastructure. The episode examines the fear index regarding job security, noting that 92% of leaders fear for their roles post-breach. Joe and Amit join Caleb to explore the evolution of personal liability for CISOs and the urgent need to move from basic visibility to deep observability. This is a forward-looking briefing for leaders who recognize that, in an era of autonomous routines, the human must remain the ultimate command-and-control center. What You’ll Learn Define the agentic paradox to understand why AI efficiency naturally compromises traditional security guardrails. Implement a three-layer framework to secure the tool, cognitive, and identity components of AI. Transition from basic visibility to deep observability to track autonomous decision-making in real time. Mitigate prompt injection risks by auditing the input and output flows of the cognitive layer. Utilize ephemeral containers to sandbox agentic tools and prevent unauthorized database alterations. Manage the elasticity of non-human identities to maintain control over rapidly spinning AI agents. Anchor AI operations with human-in-the-loop checkpoints to ensure integrity during high-stakes executions. Episode Highlights Defining the Agentic Identity and Autonomous Routines Revenue vs. Resilience: The Drivers of AI Urgency The Three-Layer Framework for Agentic Defense Shadow AI and the Rise of Invisible Insider Threats The Context Gap: Why Rolling Back AI Actions is Hard The CISO Fear Index and Personal Liability Post-Breach Visibility vs. Observability in Elastic Identity Environments
