Ashish Rajan is back on Security Unfiltered, a few years after we last recorded together at RSA. Ashish is a CISO, host of the Cloud Security Podcast and AI Security Podcast, and author of the new Wiley book AI Security Engineering.
We get into how you write a book on a field that changes every month, why agents made him rewrite his plan halfway through, and what actually matters when you have millions of agents in your environment. Ashish makes the case that logs alone can't tell you intent ("is Joe an employee?" and "can I have Joe's password?" both look like plain text), why behavior is where agent security is heading, and why no vendor is going to build the internal context layer your security team needs. We also talk open weight models vs paying for tokens, whether the government had this tech first, and why human life still comes before technology.
Chapters 00:00 Ashish is back on Security Unfiltered 02:40 Joe's dissertation: zero trust for satellites and post-quantum crypto 06:36 Ashish's new book, AI Security Engineering 07:07 Ashish's path: IAM, cloud security, Cloud Security Podcast 08:26 From media company to AI advisory and the AI Security Lab 10:19 Local compute, open weight models, Grok vs Claude 13:35 Build harnesses you can swap out 14:34 How do you write a book on a topic that changes every month? 19:05 When research gets published faster than you can cite it 20:54 Why network security is back in the conversation 21:23 Agents breaking out of a sandbox 22:57 Is the government already ahead on AI? 23:54 The Manhattan Project comparison 25:13 How cyber warfare teams test exploits 26:41 Security for AI is a new field 28:16 Human life over technology: Waymo and surgical robots 29:58 Which agent security capabilities actually work? 31:40 Make the agent explain why it pulled 10 records 32:50 Behavior and intent over logs 35:12 The internal context layer no vendor will build 38:47 Logging is legacy at AI speed 40:20 Horses vs cars: who gets left behind with AI 42:17 Wrap up
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