● Topic
AI Security
Securing LLMs, agentic systems, and enterprise AI — threats, controls, red teaming, and assurance.
16 articles · page 2 of 2
← All articlesA Control Framework for Non-Human & Agentic Identity
A practitioner control framework for governing non-human and agentic identities: eight principles, a four-tier risk model, thirty-five controls across eight domains, an agentic threat model, and a maturity model — mapped to OWASP NHI Top 10, NIST AI RMF, CSF 2.0, and 800-53.
The Non-Human Identity Reckoning — and Why Agents Make It Urgent
Non-human identities are the enterprise's largest and least-governed identity population, and AI agents just added autonomy to the problem. Here is why the next identity crisis is already here — and the discipline that answers it.
Understanding Azure AI Foundry Agent Identities, Blueprints, and Entra ID Object Relationships
A practical identity architecture guide for security, governance, and troubleshooting
AI Red Teaming: A Risk-Based Methodology for When, Why, and How
AI red teaming has emerged as a foundational security control for organizations deploying artificial intelligence — analogous to penetration testing for traditional applications, but distinct in scope, technique, and risk profile. Unlike standard security assessments, AI red teaming…
Securing Enterprise AI: An Identity-First Approach
As enterprises move from AI pilots to agentic systems that act on their behalf, identity becomes the control plane. Here is how I think about securing AI agents with the same rigor we apply to human and workload identities.
Using AI to Optimize SOC Operations
Security Operations Centers are drowning in alerts while the metrics that matter — mean time to detect and respond — barely move. Here is how AI-driven automation and analytics change the operational math.