AI Vulnerability Database

An open-source, extensible knowledge base of AI failures

Our Efforts
Submit an AI Vulnerability!


AI Vulnerability Database (AVID) is an open-source knowledge base of failure modes for Artificial Intelligence (AI) models, datasets, and systems. The goals of AVID are to
  • Build out a functional taxonomy of potential AI harms across the coordinates of security, ethics, and performance
  • House full-fidelity information (metadata, harm metrics, measurements, benchmarks, and mitigation techniques if any) on evaluation use cases of a harm (sub)category
  • Evaluate systems, models, and datasets for specific harms and persist the structured results into a single source of truth.

What We Do

Our efforts have two focus areas: a Taxonomy of the different avenues through which an AI system can fail, and a Database of evaluation examples that contain structured information on individual instances of these failure (sub)categories.
We also periodically release blog posts covering ongoing trends in AI risk management.