Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How do you explain AI Security without the jargon? Easy you make it food. In this video, we asked leading AI Security professionals to describe AI Security as a dish. Their answers turn complex ideas like prompt injection, data leaks, and model hardening into bite-sized insights you’ll actually remember. From layered lasagna to spicy tacos, each response brings a fresh perspective on what it means to build and protect secure AI systems.

AI coding assistants don’t just speed up development — they introduce two kinds of risks you can’t afford to ignore. Direct risks: vulnerabilities added straight into generated code. Indirect risks: exposure through how AI tools shape workflows, dependencies, and external connections. Both can create blind spots — and both demand visibility. Watch to learn how recognizing these layers helps secure your AI-driven workflows.

Is AI making application security easier or harder? We spoke to Amit Chita, Field CTO at Mend.io, the rise of AI agents in the Software Development Lifecycle (SDLC) presents a unique opportunity for security teams to be stricter than ever before. As developers increasingly use AI agents and integrate LLMs into applications, the attack surface is evolving in ways traditional security can't handle. The only way forward is a Zero Trust approach to your own AI models. Join Ashish Rajan and Amit Chita as they discuss the new threats introduced by AI and how to build a resilient security program for this new era.

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.