AI infrastructure security: Why it deserves its own category

Attacks on AI infrastructure are increasing, not through prompt manipulation as commonly assumed, but via the underlying systems supporting AI operations. This shift in attack vectors highlights the need for a dedicated focus on AI infrastructure security, as AI systems, though still evolving, manage massive and sensitive data, broadening the risk surface. AI's integration into modern enterprise involves diverse components such as generative and predictive systems, training and inference services, and cloud-based architectures, each with unique security challenges. The article underscores the importance of understanding the operational and architectural nuances of AI to effectively manage these risks, advocating for a comprehensive security approach that includes asset discovery, posture management, pipeline security, and runtime protection. The contrast between securing conversational inputs and the deeper infrastructure is likened to the difference between psychological and neurological assessments, emphasizing the need for robust infrastructure controls to prevent breaches.