Cloud Security Podcast
Securing AI Applications in the Cloud
What does it take to secure AI-based applications in the cloud? In this episode, host Ashish Rajan sits down with Bar-el Tayouri, Head of Mend AI at Mend.io, to dive deep into the evolving world of AI security. From uncovering the hidden dangers of shadow AI to understanding the layers of an AI Bill of Materials (AIBOM), Bar-el breaks down the complexities of securing AI-driven systems. Learn about the risks of malicious models, the importance of red teaming, and how to balance innovation with security in a dynamic AI landscape.
- What is an AIBOM and why it matters
- The stages of AI adoption: experimentation to optimization
- Shadow AI: A factor of 10 more than you think
- Practical strategies for pre- and post-deployment security
- The future of AI security with agent swarms and beyond
Guest Socials: Bar-El's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Cybersecurity Podcast
Questions asked:
(00:00) Introduction
(02:24) A bit about Bar-el
(03:32) What is AIBOM?
(12:58) What is an embedding model?
(16:12) What should Leaders have in their AI Security Strategy?
(19:00) Whats different about the AI Security Landscape?
(23:50) Challenges with integrating security into AI based Applications
(25:33) Has AI solved the disconnect between Security and Developers
(28:39) Risk framework for AI Security
(32:26) Dealing with threats for current AI Applications in production
(36:51) Future of AI Security
(41:24) The Fun Section
- Broadcast on:
- 06 Mar 2025
What does it take to secure AI-based applications in the cloud? In this episode, host Ashish Rajan sits down with Bar-el Tayouri, Head of Mend AI at Mend.io, to dive deep into the evolving world of AI security. From uncovering the hidden dangers of shadow AI to understanding the layers of an AI Bill of Materials (AIBOM), Bar-el breaks down the complexities of securing AI-driven systems. Learn about the risks of malicious models, the importance of red teaming, and how to balance innovation with security in a dynamic AI landscape.
- What is an AIBOM and why it matters
- The stages of AI adoption: experimentation to optimization
- Shadow AI: A factor of 10 more than you think
- Practical strategies for pre- and post-deployment security
- The future of AI security with agent swarms and beyond
Guest Socials: Bar-El's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Cybersecurity Podcast
Questions asked:
(00:00) Introduction
(02:24) A bit about Bar-el
(03:32) What is AIBOM?
(12:58) What is an embedding model?
(16:12) What should Leaders have in their AI Security Strategy?
(19:00) Whats different about the AI Security Landscape?
(23:50) Challenges with integrating security into AI based Applications
(25:33) Has AI solved the disconnect between Security and Developers
(28:39) Risk framework for AI Security
(32:26) Dealing with threats for current AI Applications in production
(36:51) Future of AI Security
(41:24) The Fun Section