AWS introduces an AI Security Framework for protecting AI systems

Amazon Web Services has published its own AI Security Framework built around three key aspects: the type of AI system, the architectural layer, and the lifecycle stage. Each aspect helps organizations select appropriate security controls for specific scenarios.

🛑 Types of AI Systems

AWS divides AI systems into three categories: 🟠AI applications that only generate responses; 🟠systems with access to corporate data and knowledge bases through retrieval-augmented generation (RAG), where risks include data leakage and uncontrolled access to information; 🟠AI agents capable of independently performing actions, invoking tools, working with APIs, and interacting with infrastructure.

🛑 Architectural Layers

AWS approaches AI security as a multi-layered architecture. The framework separates protection into several layers: 🟠the infrastructure layer, including compute resources, networking, storage, environment isolation, and foundational platform security; 🟠the data and model layer, covering models, training data, vector databases, access management, and data leakage protection; 🟠the application and AI agent layer, including interfaces, AI agents, connected tools, automated actions, and user interactions.

🛑 Lifecycle Stages

The framework also organizes AI security according to deployment phases.

🟠Foundational phase: from initial development to prototype. Recommended controls include access management, encryption, content filtering, auditing, and model guardrails.

🟠Enhanced phase: the transition from prototype to production deployment. At this stage, organizations introduce data classification, network security, threat detection, and incident response capabilities.

🟠Advanced phase: continuous improvement and scaling. Here, AWS focuses on security governance, continuous compliance, security testing, and digital forensics.

Overall, AI systems are increasingly being treated as full-fledged infrastructure components, with their own attack surface, access to sensitive data, and the ability to perform actions within enterprise environments.

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