Can Generative AI Be Secured? Amazon's Chief Security Officer Weighs In

In this episode of Eye on AI, Amazon's Chief Security Officer Stephen Schmidt pulls back the curtain on how Amazon is using AI-powered cybersecurity to defend against real-world threats. From global honeypots to intelligent alarm systems and secure AI agent networks, Steve shares never-before-heard details on how Amazon is protecting both its infrastructure and your data in the age of generative AI.

We dive deep into:

• Amazon's MadPot honeypot network and how it tracks adversaries in 90 seconds

• The role of AI in threat detection, alarm triage, and code validation

• Why open-source vs. closed-source models are a real security debate

• The critical need for data privacy, secure LLM usage, and agent oversight

• Amazon's $5M+ Nova Trusted AI Challenge to battle adversarial code generation

Whether you're building AI tools, deploying models at scale, or just want to understand how the future of cybersecurity is evolving—this episode is a must-listen.

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(00:00) Preview

(00:52) Stephen Schmidt's Role and Background at Amazon

(02:11) Inside Amazon's Global Honeypot Network (MadPot)

(05:26) How Amazon Shares Threat Intel Through GuardDuty

(08:06) Are Cybercriminals Using AI?

(10:28) Open Source vs Closed Source AI Security Debate

(13:09) What Is Amazon GuardDuty

(17:44) How Amazon Protects Customer Data at Scale

(20:18) Can Autonomous AI Agents Handle Security?

(25:14) How Amazon Empowers SMBs with Agent-Driven Security

(26:18) What Tools Power Amazon's Security Agents?

(29:25) AI Security Basics

(35:34) Securing AI-Generated Code

(37:26) Are Models Learning from Our Queries?

(39:44) Risks of Agent-to-Agent Data Sharing

(42:08) Inside the $5M Nova Trusted AI Security Challenge

(47:01) Supply Chain Attacks and State Actor Tactics

(51:32) How Many True Adversaries Are Out There?

(53:04) What Everyone Needs to Know About AI Security