A practitioner's deep dive into building a real generative AI governance program — from policy to controls to board reporting If you read my earlier post, Generative AI Governance: Using the NIST Framework to Build Trust, Reduce Risk, and Lead Secure AI Adoption , you got a solid introduction to why the NIST AI Risk Management Framework (AI RMF) matters and how its four core functions — Govern, Map, Measure, and Manage — provide a structure for responsible AI adoption. That post was intentionally high-level. This one is not. Over the past two-plus decades in security leadership, I have watched organizations repeatedly make the same mistake with emerging technology: they adopt first and govern later. We did it with cloud. We did it with mobile. We are doing it right now with generative AI — and the consequences are more significant than most leadership teams realize. Generative AI is not just another SaaS tool your employees are using without IT approval. It is a...
InfoSec Made Easy OT Security Leadership | NCSC Guidance Series Reducing attack surface in OT environments — why how you connect matters as much as whether you connect In cybersecurity, the concept of attack surface is well understood: the more accessible your systems are to potential adversaries, the more opportunity exists for exploitation. In IT environments, attack surface management has become a mature discipline, with tools, processes, and dedicated teams focused on identifying and reducing unnecessary exposure. In OT environments, the same concept applies — but the stakes, the constraints, and the practical approaches are significantly different. Principle 2 of the NCSC's Secure Connectivity Principles for Operational Technology is focused on exposure management: proactively identifying, assessing, and mitigating the risks associated with how accessible your OT assets are to external or adjacent networks. The principle is built around a straightforward...