AIDEFEND (Artificial Intelligence Defense Framework) is an open knowledge base dedicated to AI security, providing defensive countermeasures and best practices to help security pros safeguard AI and machine learning systems.
Practicality is at the core of AIDEFEND. The framework is designed to be “highly actionable,” with the goal of not only raising awareness of threats but also providing clear playbooks to defend against them.
“Each technique and subtechnique is mapped to concrete threats cataloged in MITRE ATLAS, MAESTRO, and the OWASP Top 10 lists for LLMs and ML. Just as important, the project is open source, intentionally built as a living knowledge base for the entire community to use and contribute to,” Edward Lee, the creator of AIDEFEND, told Help Net Security.
Future plans and download
Lee’s top priority is to “continuously expand and refine the techniques and subtechniques based on new threat intelligence and defensive research that emerges.”
Beyond that, the author is exploring more granular, topic-focused views and defensive playbooks, bundling techniques for areas such as agentic AI, multimodal systems, and edge AI security so users with specific use cases can access tailored guidance. He also plans to expand integrations with other organizations’ work and remain open to new ideas as the project develops.
AIDEFEND is available for free on GitHub.
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