The post explains how to adapt threat modeling for AI systems, which differ from traditional software in that they produce probabilistic outputs, follow instructions, and have expanded attack surfaces. It recommends explicitly defining what assets the system must protect, understanding real usage patterns, and identifying risks such as prompt injection, misuse of tools, data integrity failures, and harmful outputs. It concludes that AI threat modeling requires structured analysis early in design to assess likelihood and impact and inform architectural mitigations.
https://www.microsoft.com/en-us/security/blog/2026/02/26/threat-modeling-ai-applications/