Microsoft SDL: Evolving security practices for an AI-powered world

Microsoft describes an expanded Secure Development Lifecycle (SDL) for AI that addresses AI-specific risks—including prompt injection, data poisoning, memory and cache exposure, and governance challenges—and emphasizes a multidisciplinary, iterative approach grounded in research, policy, standards, enablement, collaboration, and continuous improvement. The post highlights key focus areas such as AI threat modeling, observability, memory protections, agent identity/RBAC, model publishing, and shutdown mechanisms, positioning the framework as a practical guide for building resilient and trustworthy AI systems amid rapidly evolving threats.