A Conversation with Bar-El Tayouri from Mend.io

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May 6, 2025

Bar-El Tayouri, Head of AI Security at Mend.io, specializes in the intersection of application and AI security. He discusses the challenges traditional AppSec faces in the AI era, emphasizing the need for comprehensive risk assessment and mitigation strategies. The conversation dives into innovative threat discovery techniques, including simulating dynamic attacks and the importance of security integrated into development workflows. Tayouri also highlights the evolving landscape of identity management and security in multi-agent systems, urging a reevaluation of existing governance practices.

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ANECDOTE

Early Tech Journey and Growth

Bar-el Tayouri began coding at age 12, focusing initially on game development and hacking scores.
His early experiences evolved into expertise in network security, cryptography, and eventually AI security at Mend.io.

INSIGHT

AI Components as AppSec Risk

AI components inside applications are the biggest emerging risk in application security.
Usage of AI by employees for productivity has less risk compared to embedded AI components and agents in production apps.

INSIGHT

MCP Servers' Unique Risks

MCP servers differ mainly by their usage and close connection to critical data.
Their fuzzy text-based interfaces make it impossible to fully define input-output interactions as in traditional APIs.

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In this episode, I speak with Bar-El Tayouri, Head of AI Security at Mend.io, about the rapidly evolving landscape of application and AI security—especially as multi-agent systems and fuzzy interfaces redefine the attack surface.

We talk about:

• Modern AppSec Meets AI Agents
How traditional AppSec falls short when it comes to AI-era components like agents, MCP servers, system prompts, and model artifacts—and why security now depends on mapping, monitoring, and understanding this entire stack.

• Threat Discovery, Simulation, and Mitigation
How Mend’s AI security suite identifies unknown AI usage across an org, simulates dynamic attacks (like prompt injection via PDFs), and provides developers with precise, in-code guidance to reduce risk without slowing innovation.

• Why We’re Rethinking Identity, Risk, and Governance
Why securing AI systems isn’t just about new threats—it’s about re-implementing old lessons: identity access, separation of duties, and system modeling. And why every CISO needs to integrate security into the dev workflow instead of relying on blunt-force blocking.

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Chapters:

00:00 - From Game Hacking to AI Security: Barel’s Tech Journey
03:51 - Why Application Security Is Still the Most Exciting Challenge
04:39 - The Real AppSec Bottleneck: Prioritization, Not Detection
06:25 - Explosive Growth of AI Components Inside Applications
12:48 - Why MCP Servers Are a Massive Blind Spot in AI Security
15:02 - Guardrails Aren’t Keeping Up With Agent Power
16:15 - Why AI Security Is Maturing Faster Than Previous Tech Waves
20:59 - Traditional AppSec Tools Can’t Handle AI Risk Detection
26:01 - How Mend Maps, Discovers, and Simulates AI Threats
34:02 - What Ideal Customers Ask For When Securing AI
38:01 - Beyond Guardrails: Mend’s Guide Rails for In-Code Mitigation
41:49 - Multi-Agent Systems Are the Next Security Nightmare
45:47 - Final Advice for CISOs: Enable, Don’t Disable Developers

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