Identity Management Challenges for AI Agents

This white paper addresses the challenges of identity management, authentication, and authorization in the context of AI agents. It highlights the urgent need for best practices in these areas due to the rapid rise of AI agents that operate autonomously and interact with external services. The document outlines existing frameworks and protocols, such as the Model Context Protocol (MCP) and OAuth 2.1, which are currently used for managing AI agents. However, it also points out their limitations, particularly in cross-domain and asynchronous scenarios. The paper discusses the potential risks associated with agent identity fragmentation, user impersonation, and scalability issues in human oversight. Furthermore, it emphasizes the importance of establishing user-centric consent models and robust security profiles to facilitate safe AI adoption. The document serves as a strategic agenda for stakeholders involved in AI and access management, aiming to provide guidance on securing AI agents and addressing foundational identity management issues for future autonomous systems.