Guest:

• Christine Sizemore, Cloud Security Architect, Google Cloud

Topics:

• Can you describe the key components of an AI software supply chain, and how do they compare to those in a traditional software supply chain?
• I hope folks listening have heard past episodes where we talked about poisoning training data. What are the other interesting and unexpected security challenges and threats associated with the AI software supply chain?
• We like to say that history might not repeat itself but it does rhyme – what are the rhyming patterns in security practices people need to be aware of when it comes to securing their AI supply chains?
• We’ve talked a lot about technology and process–what are the organizational pitfalls to avoid when developing AI software? What organizational "smells" are associated with irresponsible AI development?
• We are all hearing about agentic security – so can we just ask the AI to secure itself?
• Top 3 things to do to secure AI software supply chain for a typical org?

Resources:

• Video
• “Securing AI Supply Chain: Like Software, Only Not” blog (and paper)
• “Securing the AI software supply chain” webcast
• EP210 Cloud Security Surprises: Real Stories, Real Lessons, Real "Oh No!" Moments
• Protect AI issue database
• “Staying on top of AI Developments”
• “Office of the CISO 2024 Year in Review: AI Trust and Security”
• “Your Roadmap to Secure AI: A Recap” (2024)
• "RSA 2025: AI’s Promise vs. Security’s Past — A Reality Check" (references our "data as code" presentation)

Hosts:

• David Homovich, Customer Advocacy Lead, Office of the CISO, Google Cloud
• Nick Godfrey, Senior Director and Head of Office of the CISO, Google Cloud

Guests:

• Don Callahan, Advisor and Board Member

Resources:

• EP3 Don Callahan on Emerging Technology (as aired originally)
• The Cyber-Savvy Boardroom podcast site
• The Cyber-Savvy Boardroom podcast on Spotify
• The Cyber-Savvy Boardroom podcast on Apple Podcasts
• The Cyber-Savvy Boardroom podcast on YouTube
• Now hear this: A new podcast to help boards get cyber savvy (without the jargon)

Guest:

• Diana Kelley, CSO at Protect AI

Topics:

• Can you explain the concept of "MLSecOps" as an analogy with DevSecOps, with 'Dev' replaced by 'ML'? This has nothing to do with SecOps, right?
• What are the most critical steps a CISO should prioritize when implementing MLSecOps within their organization? What gets better when you do it?
• How do we adapt traditional security testing, like vulnerability scanning, SAST, and DAST, to effectively assess the security of machine learning models? Can we?
• In the context of AI supply chain security, what is the essential role of third-party assessments, particularly regarding data provenance?
• How can organizations balance the need for security logging in AI systems with the imperative to protect privacy and sensitive data? Do we need to decouple security from safety or privacy?
• What are the primary security risks associated with overprivileged AI agents, and how can organizations mitigate these risks?
• Top differences between LLM/chatbot AI security vs AI agent security?

Resources:

• “Airline held liable for its chatbot giving passenger bad advice - what this means for travellers”
• “ChatGPT Spit Out Sensitive Data When Told to Repeat ‘Poem’ Forever”
• Secure by Design for AI by Protect AI
• “Securing AI Supply Chain: Like Software, Only Not”
• OWASP Top 10 for Large Language Model Applications
• OWASP Top 10 for AI Agents (draft)
• MITRE ATLAS
• “Demystifying AI Security: New Paper on Real-World SAIF Applications” (and paper)
• LinkedIn Course: Security Risks in AI and ML: Categorizing Attacks and Failure Modes