How to Detect Threats to AI Systems with MITRE ATLAS Framework

The MITRE Adversarial Threat Landscape for Artificial Intelligence Systems (ATLAS) framework is a knowledge base of documented and categorized cyber threats against AI systems, detailing 14 adversarial tactics used by digital adversaries. MLOps monitoring is the continuous process of monitoring, tracking, and observing ML models deployed in production environments to detect security threats against AI systems. The MITRE ATLAS framework can be used with MLOps monitoring to help detect cyber threats against AI systems, including data poisoning, ML evasion attacks, supply chain compromise, LLM plugin compromise, and LLM prompt injection.