MITRE ATLAS & AI Security
Understand adversarial threats against AI systems and strengthen your security posture with MITRE ATLAS.
What Is MITRE ATLAS?
MITRE ATLAS (Adversarial Threat Landscape for AI Systems) is a publicly accessible knowledge base documenting adversary tactics and techniques targeting AI-enabled systems. It draws on security research, observed attacks, and realistic demonstrations to help organizations understand how AI systems can be compromised or manipulated.
Modeled after MITRE ATT&CK, ATLAS provides a structured way to examine AI-specific threats, explore defensive mitigations, and inform security assessments. It supports AI threat modeling and adversarial testing but is not a regulation, certification, or mandatory compliance standard.
What Does MITRE ATLAS Cover?
Explore the core components of MITRE ATLAS that help organizations examine and mitigate adversary behavior targeting AI-enabled systems.
Tactics
The objectives an adversary seeks to achieve. Help teams understand the purpose behind an attack.
Techniques
Methods adversaries use to achieve their objectives. Help identify potential attack paths and weaknesses.
Sub-techniques
More specific variations of an attack technique. Provide greater detail for threat analysis and testing.
Mitigations
Defensive measures that can reduce the likelihood or impact of attacks. Inform security controls and mitigation planning.
Case Studies
Documented incidents and demonstrations of adversarial behavior. Help teams learn from observed attacks and realistic scenarios.
MITRE ATLAS at a Glance
Get a quick overview of MITRE ATLAS, including its scope, publisher, and core security use cases.
Who Should Consider MITRE ATLAS?
MITRE ATLAS is relevant to security teams, engineers, and architects designing, testing, and defending AI-enabled systems.
AI Security Teams
Identify adversarial techniques relevant to AI deployments and use them to inform defensive strategies.
AI and ML Engineers
Understand potential attacks against models, datasets, inference endpoints, and AI pipelines.
Application Security Teams
Assess vulnerabilities in LLM applications, AI integrations, and connected services.
Security Architects
Incorporate AI-specific attack paths into architecture reviews and threat models.
Red Teams and Penetration Testers
Develop adversarial scenarios to evaluate AI system resilience and test security controls.
SOC and Threat Intelligence Teams
Use ATLAS techniques to inform threat detection, incident investigation, and response planning.
AI Agent Developers
Assess risks involving agent autonomy, tool access, permissions, and interactions with external systems.
Enterprise Security Leaders
Use adversary-informed threat analysis to support AI security strategy and prioritize defensive investments.
MITRE ATLAS Readiness Checklist
MITRE ATLAS & AI Security
AI systems introduce attack surfaces that extend beyond conventional application vulnerabilities. Models can be manipulated through inputs, connected tools can introduce additional risks, and agents may perform actions across systems and data sources. MITRE ATLAS helps organizations understand these adversarial techniques and use that knowledge to inform their security controls.
Defend Against Prompt Injection
Malicious instructions can manipulate model behavior, bypass intended safeguards, or influence how an AI application uses connected tools. Understanding relevant attack techniques helps teams develop realistic tests and evaluate their defenses.
Protect Sensitive Information
AI systems may expose confidential information through generated responses, retrieved context, connected applications, or compromised workflows. ATLAS can help teams investigate adversarial techniques that target data access and extraction.
Secure AI Agents & Connected Tools
AI agents can interact with APIs, retrieve information, and execute actions through external tools. ATLAS includes techniques involving agent tools, autonomous behavior, and agent environments that can inform security assessments of these systems.
Strengthen AI Supply Chain Security
Models, datasets, software dependencies, and third-party tools can introduce risks into AI environments. Understanding supply chain attack techniques helps organizations assess dependencies and identify where additional verification or controls may be needed.
Improve Threat Detection
ATLAS provides a structured vocabulary for describing adversary behavior. Security teams can use it to inform detection rules, investigation workflows, and incident response procedures for AI-enabled systems.
Validate Security Controls
Organizations can translate relevant ATLAS techniques into adversarial test scenarios and assess whether their controls work as intended. Testing should reflect the organization's architecture, exposure, and risk profile.
How MITRE ATLAS Fits Into the AI Security Landscape
MITRE ATLAS focuses on adversarial threats against AI systems. Other frameworks and resources complement it by addressing conventional cyber threats, application-level vulnerabilities, and broader AI risk management and governance.
MITRE ATT&CK
MITRE ATT&CK documents adversary tactics and techniques across conventional enterprise and other computing environments. ATLAS complements ATTACK by focusing on adversarial behavior involving AI systems and AI-enabled capabilities. Organizations can use both to assess traditional infrastructure threats alongside AI-specific attack paths.
OWASP GenAI / LLM Security Guidance
OWASP provides security guidance for LLM applications and generative AI systems, covering vulnerabilities such as prompt injection, sensitive information disclosure, and excessive agency. It can complement ATLAS by helping development and security teams assess application-level weaknesses.
NIST AI Risk Management Framework
NIST AI RMF provides a broader approach to managing AI risks through Govern, Map, Measure, and Manage. ATLAS can help organizations identify concrete adversarial threats that inform risk assessments, security testing, and mitigation planning.
ISO/IEC 42001
ISO/IEC 42001 establishes requirements for an Artificial Intelligence Management System. It provides a structured approach to AI governance, risk management, and continual improvement, while ATLAS can inform the technical threat assessments supporting an AI security program.
Frequently Asked Questions
Official MITRE ATLAS Resources
For authoritative information, data feeds, and community resources about MITRE ATLAS and AI risk management, refer to the official documentation:
MITRE ATLAS & AI
Turn AI Threat Intelligence Into Action
Build the visibility and security controls needed to identify threats and protect your AI environment.