Identity Security in the Era of AI and NHIs (Non-Human Identities)
The New Identity Crisis Cybersecurity used to be about people. Securing digital identities meant managing employee access, verifying user credentials, and assigning roles. But today, that human-centric approach no longer suffices. With the explosive growth of cloud services, DevOps pipelines, and especially artificial intelligence, we are seeing an identity paradigm shift. Enterprises now manage thousands even millions of Non-Human Identities (NHIs): service accounts, containers, scripts, bots, and AI agents. In some organizations, NHIs outnumber human users by 50 to 1. Identity is the new security perimeter. Across modern digital ecosystems, machines have overtaken humans as the dominant identity type. Yet most identity frameworks still prioritize people, creating a dangerous blind spot. Understanding NHIs: The Rise of Machine Identities Non-Human Identities (NHIs) refer to any digital identity used by systems, software, or hardware, rather than people, to interact with services and data. These identities operate silently, scale rapidly, and often remain unnoticed. Common examples include: Unlike human users, NHIs lack formal onboarding and offboarding processes. Once created, they often persist indefinitely, even when no longer in use, becoming “shadow identities” with unknown access and unknown owners. AI’s Role in Expanding the Identity Surface Artificial Intelligence is not just consuming data; it is reshaping the identity landscape. AI introduces both volume and volatility into identity ecosystems. Unlike traditional human users, AI-generated entities are dynamic, fast-scaling, and often operate beyond formal visibility. Consider: Each of these non-human actors requires access credentials and needs them in real time. The issue arises when these identities are created outside structured IAM processes. They may be spun up automatically, use temporary containers, or be embedded within code, making them difficult to track or govern. This leads to credential sprawl, inconsistent permissioning, and limited visibility. These entities not only expand the identity surface but also redefine it. As AI-driven processes multiply, they quietly widen the attack surface, often without triggering any alarms until a breach occurs. Key Identity Security Challenges The rise of NHIs calls for a new approach to identity security, one that treats machine identities as first-class citizens and addresses risks that traditional IAM models cannot handle. Rethinking Identity Security for the AI Age Securing NHIs requires a new mindset. Identity must become the foundation of security, not merely a function of user management. Key shifts include: Modern Tools and Techniques Leading organizations are investing in modern identity platforms that go beyond managing human users: Real-World Lessons from Breaches Security failures involving NHIs are no longer theoretical. Consider: These cases emphasize the need for rigorous NHI governance and proactive detection methods. AI’s New Identity Threats As AI systems become more autonomous and embedded in decision-making, they do not just consume identities—they can generate, manipulate, or misuse them. This introduces a novel risk class. New Threat Vectors: “AI is no longer just consuming identities – it is beginning to manipulate them. Modern security systems must detect not only access abuse but also access deception.” – Dineshkumar Gandhi, Technical Project Manager at SISAR CISO Action Plan: Identity-First Security
