MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a comprehensive, publicly available knowledge base and framework that documents the tactics, techniques, and case studies of adversarial attacks targeting artificial intelligence (AI) and machine learning (ML) systems. Modeled after the MITRE ATT&CK framework, ATLAS organizes real-world observations of how adversaries compromise AI systems, including methods like data poisoning, model evasion, and model inversion. The framework categorizes 14 main adversarial tactics and provides detailed examples of techniques used to exploit AI vulnerabilities, helping organizations anticipate, detect, and defend against these evolving threats. ATLAS serves as a critical resource for security professionals, AI developers, and researchers to strengthen AI security and foster collaboration in the face of rapidly advancing AI-driven risks.
Publication's URL
URL: https://atlas.mitre.org/Publication's scorecard
Country: USA
Scope: Cyber
Typology: Framework
Publication's date: March 13, 2025
Category: Threat Intel
Sector: Cross-Sector
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