What is MITRE ATLAS?

MITRE ATLAS is a knowledge base that documents tactics, techniques, and procedures used in attacks against artificial intelligence (AI) and machine learning (ML) systems. Understanding what is MITRE ATLAS helps security teams identify AI-specific threats, evaluate potential attack paths, and strengthen defenses across the AI lifecycle. As organizations increasingly adopt AI technologies, security teams need frameworks that address risks beyond traditional cybersecurity threats.

Why was MITRE ATLAS created?

Traditional security frameworks primarily focus on networks, endpoints, applications, and user behavior. AI systems introduce unique attack surfaces that require additional security considerations.

MITRE developed ATLAS to help organizations understand how attackers may target machine learning models, training data, inference processes, and supporting infrastructure.

Organizations use the framework to:

• Study AI-specific attack techniques
• Support threat modeling activities
• Improve AI security awareness
• Evaluate defensive controls
• Understand emerging AI attack patterns

This approach helps security teams assess risks throughout the AI lifecycle.

How does MITRE ATLAS work?

The framework organizes adversarial behaviors into tactics and techniques that describe how attackers interact with AI systems. A typical workflow involves:

• Identifying AI assets and components
• Mapping potential attack techniques
• Evaluating exposure across the AI lifecycle
• Assessing existing security controls
• Prioritizing defensive improvements
• Monitoring for suspicious activity

This structured approach helps organizations understand how AI systems could be targeted in real-world scenarios.

Which attack areas does MITRE ATLAS cover?

AI systems face risks that differ from traditional software environments. Attackers may attempt to manipulate data, influence model behavior, or compromise supporting infrastructure.

The framework commonly addresses the following areas:

These attack categories help organizations evaluate risks throughout model development and deployment processes.

How can organizations use MITRE ATLAS?

Security teams often integrate AI-focused threat knowledge into broader security programs. The framework can support planning, assessment, and security review activities.

Common use cases include:

• AI threat modeling
• Security training programs
• Risk assessments
• Control validation exercises
• Incident response preparation

Organizations can use these insights to better understand how attackers may target AI environments and supporting infrastructure.

Investigating security events in AI environments

AI systems rely on underlying endpoints, servers, and infrastructure that require ongoing monitoring and investigation. When suspicious activity affects systems supporting AI workloads, security teams need visibility into related events and endpoint behavior.

Hexnode XDR supports investigation workflows by helping analysts review incident details, examine endpoint activity, perform endpoint scans, access remote terminal capabilities when appropriate, and gather additional context during security investigations.

These capabilities can help teams investigate incidents affecting the infrastructure that supports AI and machine learning operations.