AI Security Reality Check

Nathan Hamiel, Head of Research at Kudelski Security, joins Rohit Raveendran for an essential reality check on AI security in DevOps environments. This candid conversation cuts through the hype to address real-world threats, vulnerabilities, and practical defense strategies that every team integrating AI into their infrastructure should understand.

Real-World AI Security Threats

Explore the actual security landscape facing organizations adopting AI, from model poisoning and prompt injection attacks to data exfiltration risks. Nathan shares insights from Kudelski Security's research into emerging threat vectors and how attackers are targeting AI-powered systems in production environments.

DevOps-Specific Vulnerabilities

Understand the unique security challenges that arise when AI meets DevOps workflows, including supply chain risks, model integrity issues, and the security implications of AI-generated infrastructure code. Learn how traditional security practices need to evolve for AI-augmented development pipelines.

Practical Defense Strategies

Get actionable guidance on implementing robust security measures for AI in DevOps, including model validation techniques, secure prompt engineering practices, and monitoring strategies for AI-powered infrastructure operations. Discover how to balance innovation with security requirements.

Industry Insights and Trends

Benefit from Nathan's perspective on the evolving threat landscape, emerging security standards for AI systems, and what organizations should prioritize when building security into their AI-driven DevOps practices.

Key Takeaways for Teams

Learn how to assess AI security risks in your current environment, implement baseline security controls for AI systems, and build a security-first culture around AI adoption without stifling innovation.

Essential listening for security professionals, DevOps engineers, platform teams, and anyone responsible for safely integrating AI into production infrastructure and development workflows.