Peter Bailey, SVP and GM of Cisco Security with deep incident response and AI experience, explains how agentic AI is expanding the attack surface at machine speed. He outlines risks like shadow MCP servers, agents touching PII, and why perimeter controls fail. He also covers model provenance, agent identity and dynamic authorization, plus network controls like SD-WAN and SASE for AI traffic visibility.
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insights INSIGHT
Rapid Agent Adoption Then Pullback
Agent adoption exploded then halted as CISOs put 'shields up' after seeing risky behavior.
Unmanaged agents accessed PII and internal systems, expanding the attack surface at machine speed.
question_answer ANECDOTE
Developer Exposed LLM Accessing Sensitive Data
Peter described a recent incident where a developer unknowingly exposed an LLM and it accessed credit cards and sensitive data.
The story shows both agent power and the immediate security consequences of careless deployments.
insights INSIGHT
Agents Widen The Attack Surface
Agents widen attack surface by increasing entry points and exploiting seams between controls.
Purpose-built malicious agents will collapse attackers' cost curve and scale sophisticated attacks.
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In this video David speaks to Peter Bailey (SVP and GM of Cisco’s Security business). AI agents are moving fast inside enterprises, and CISOs are hitting the brakes for one reason: the attack surface is expanding at machine speed. In this interview, we break down how agentic AI changes security, why MCP servers and agent tool access create new risks, and what a zero trust approach looks like when the “user” is a non-deterministic agent. We cover real-world problems like shadow MCP servers, agents touching sensitive systems and PII, and why traditional perimeter controls and firewalls are not enough when traffic is encrypted and actions happen too quickly downstream.
You’ll also hear what Cisco is doing across the AI lifecycle: AI Defense for model scanning, provenance and guardrails, plus new protections focused on agent identity, dynamic authorization, behavior monitoring, and revocation. On the networking side, we discuss how SD-WAN and secure access (SASE) can add visibility and policy control for AI usage, including prioritizing latency-sensitive AI traffic while still enforcing security. If you’re a
security engineer, network engineer, or CISO trying to move from AI hype to safe deployment, this video gives you a practical mental model and the controls to start building now.
Big thank you to @Cisco for sponsoring this video and for sponsoring my trip to Cisco Live Amesterdam.
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// MENU //
0:00 - Coming Up
0:30 - Introduction
01:15 - CISOs Problems with AI
02:35 - Real Issues with AI Agents
04:29 - Growth of the Attack Surface
05:34 - Concern of Poisoned AI and MCP
08:09 - What is the Kill-chain
10:16 - AI with Built-in Security
11:56 - Best Practises for AI Security
14:08 - Cisco Innovations for AI
16:48 - Cisco’s Red Team for own AI
18:27 - Secure AI in Public Places
20:09 - Should You get into Cyber Security
21:26 - Advice To Your Younger Self
22:29 - Outro
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Disclaimer: This video is for educational purposes only.
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