# AADAPT

**Repository Path**: mirrors_mitre/AADAPT

## Basic Information

- **Project Name**: AADAPT
- **Description**: Adversarial Actions in Digital Asset Payment Technologies
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-06-26
- **Last Updated**: 2026-05-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ATLAS

MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems), is a knowledge base of adversary tactics, techniques, and case studies for machine learning (ML) systems based on real-world observations, demonstrations from ML red teams and security groups, and the state of the possible from academic research.

ATLAS is modeled after the MITRE ATT&CK® framework and its tactics and techniques are complementary to those in ATT&CK.  Machine learning is increasingly used across a variety of industries and there are a growing number of vulnerabilities.  We developed ATLAS to raise awareness of these threats and present them in a way familiar to security researchers.

Visit the ATLAS website at https://atlas.mitre.org!