Domain 3: AI Model Development and Security

Assessment of secure AI model development practices, vulnerability testing, and model security controls

Domain Overview

AI Model Development and Security focuses on the secure development, testing, and maintenance of AI models throughout their lifecycle. This domain addresses secure development practices, vulnerability testing, supply chain security, and model documentation to ensure AI models are developed and maintained securely.

Secure AI model development is essential as AI systems face unique security challenges beyond traditional software, including adversarial attacks, model poisoning, and inference manipulation. Organizations must implement specialized security controls and testing methodologies to protect AI models from these emerging threats.

Assessment Areas

3.1 Secure AI Model Development Lifecycle

Evaluation of the organization's AI model development lifecycle, including security requirements, threat modeling, and security testing at each phase.

Key Control: ISO 42001 Section 8.1, NIST AI RMF (MANAGE function)

Organizations should implement a secure AI model development lifecycle that includes security requirements, threat modeling, and security testing at each phase.

3.2 AI Model Documentation and Version Control

Assessment of documentation practices for AI models, including architecture, parameters, training methods, and version control.

Key Control: ISO 42001 Section 7.5, CIS Control 2

Organizations should establish standardized documentation practices for AI models, including architecture, parameters, training methods, and version control.

3.3 AI Model Security Testing

Evaluation of security testing practices for AI models, including adversarial testing, input validation, and output filtering.

Key Control: CIS Control 16, NIST CSF 2.0 (PROTECT function)

Organizations should implement comprehensive security testing for AI models, including adversarial testing, input validation, and output filtering.

3.4 AI Supply Chain Risk Management

Assessment of supply chain risk management practices for AI components, including vendor assessment and component verification.

Key Control: CIS Control 15, NIST CSF 2.0 (IDENTIFY function)

Organizations should develop and implement a supply chain risk management program for AI components, including vendor assessment and component verification.

3.5 Secure Model Updates and Versioning

Evaluation of processes for secure model updates, including testing, approval, and rollback capabilities.

Key Control: CIS Control 7, ISO 42001 Section 8.1

Organizations should establish formal processes for secure model updates, including testing, approval, and rollback capabilities.

3.6 Third-Party AI Model Security Assessment

Assessment of security assessment practices for third-party AI models, including documentation review, testing, and compliance verification.

Key Control: CIS Control 15, NIST AI RMF (MEASURE function)

Organizations should implement a program for regular security assessments of third-party AI models, including documentation review, testing, and compliance verification.

Compliance Considerations

Emerging AI Security Threats

AI models face unique security threats that organizations must address:

  • Adversarial attacks (manipulating inputs to cause misclassification)
  • Model poisoning (corrupting training data to influence model behavior)
  • Model inversion attacks (extracting training data from models)
  • Membership inference attacks (determining if data was used in training)
  • Prompt injection attacks (manipulating prompts to bypass safeguards)

Industry Standards

Several industry standards provide guidance on AI model security:

  • OWASP AI Security Top 10
  • MITRE ATLAS (Adversarial Threat Landscape for AI Systems)
  • ISO/IEC 42001 (AI Management System)
  • NIST AI Risk Management Framework
  • CIS Controls (especially Controls 7, 15, and 16)

Quick Assessment

Answer these key questions to quickly evaluate your AI model security maturity:

Quick Assessment Result

Your organization appears to be at a basic level of AI model security maturity.

Next steps: Implement a secure AI model development lifecycle and basic security testing.

Take Full Assessment

Resources

Downloads

  • Model Domain Checklist
  • Full Assessment Package
  • Question Matrix

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