AI Defense Matrix: an open framework for defending AI systems (aidefensematrix.com)

The AI Defense Matrix has been introduced as a comprehensive framework designed to enhance the security of AI systems, aligning with the NIST Cybersecurity Framework (CSF) 2.0. Created by Lenny Zeltser and Sounil Yu, this framework categorizes AI-specific assets into rows, corresponding to NIST CSF functions like identifying, protecting, and recovering. The framework offers a clear view of security gaps, assigns ownership, and helps organizations implement tailored controls to safeguard their AI systems. It can be downloaded in various formats, including CSV, YAML, and Markdown, making it accessible for integration into existing security protocols. This development is significant for the AI/ML community as it addresses critical security considerations unique to AI technologies, which traditional cybersecurity frameworks often overlook. With the increasing prevalence of AI systems in business operations, vulnerabilities such as model-loading supply chain attacks and prompt-injection risks necessitate specialized security measures. The Matrix encourages organizations to rigorously assess their current capabilities, identify shortcomings, and prioritize enhancements based on AI-specific risks, laying a foundation for developing effective security strategies tailored to the evolving landscape of artificial intelligence.