AI Agent Audit Toolkit An audit framework for AI systems implementing ISACA AI Audit Toolkit and NIST AI Risk Management Framework methodologies.
Overview The AI Agent Audit Toolkit provides a structured approach to AI compliance and control assessment designed for AI developers, IT auditors, and compliance professionals. This toolkit integrates multiple established frameworks to provide comprehensive AI system auditing capabilities.
Key Features Multi-Framework Support: Implements ISACA AI Audit Toolkit and NIST AI 600-1 GAI Risk Management Framework 20 Control Families: Comprehensive coverage including Adversarial Defense, AI Bias Mitigation, Data Privacy, and Model Governance 12 GAI Risk Categories: Complete NIST risk assessment including CBRN Information, Confabulation, and Data Privacy risks 6 Explainability Dimensions: Rationale, Responsibility, Data, Fairness, Safety & Performance, and Impact assessments Automated Assessment Engine: Real-time evidence collection and compliance evaluation Regulatory Compliance: Support for EU AI Act, NIST 800-53, ISO/IEC 27001, and other frameworks Continuous Monitoring: Real-time risk monitoring with automated alerting Enterprise Integration: APIs for integration with existing AI/ML platforms and security tools Architecture The toolkit is built using:
Java 17+ with Spring Boot 3.5+ framework Multi-database support (PostgreSQL, MongoDB, Redis) RESTful APIs with OpenAPI 3.0 documentation Microservices architecture with event-driven processing Spring Security with OAuth 2.0/JWT authentication Framework Integration ISACA AI Audit Toolkit 20 Control Families spanning diverse domains 6 Explainability Dimensions for comprehensive assessment Evidence-based control evaluation methodology Integration with established security frameworks NIST AI 600-1 GAI Risk Management Framework 12 Primary GAI Risk Categories Four AI RMF Functions (Govern, Map, Measure, Manage) Lifecycle-based risk management approach Stakeholder-specific action implementation Quick Start Prerequisites Java 17 or higher Maven 3.6+ or Gradle 7+ PostgreSQL 12+ (primary database) MongoDB 4.4+ (document storage) Redis 6+ (caching) Installation Clone the repository: git clone https://github.com/[repository-url]/ai-agent-audit-toolkit.git cd ai-agent-audit-toolkit Configure databases in application.yml
Build and run:
./gradlew bootRun Access the application at http://localhost:8080 API Documentation Once running, access the API documentation at:
Swagger UI: http://localhost:8080/swagger-ui.html OpenAPI Spec: http://localhost:8080/v3/api-docs Core Components Framework Module Risk Management: NIST GAI risk assessment and scoring Control Assessment: ISACA control family implementation Explainability Engine: Six-dimension assessment framework Lifecycle Management: AI system lifecycle tracking Assessment Engine Multi-methodology Support: ISACA, NIST, and hybrid approaches Automated Evidence Collection: Integration with AI systems Dynamic Test Execution: Explainability-driven assessment Compliance Mapping: Multi-framework regulatory compliance Governance Module Policy Management: AI governance with version control Regulatory Compliance: EU AI Act, NIST, ISO compliance tracking Accountability Framework: Responsibility matrices and ownership Monitoring Module Real-time Risk Monitoring: Continuous GAI risk assessment Performance Metrics: Safety, fairness, and performance tracking Compliance Dashboards: Real-time multi-framework status Development Roadmap Phase 1: Foundation (Months 1-3) Core framework implementation Basic assessment engine Database schema and API foundation Authentication and authorization Phase 2: Assessment Capabilities (Months 4-6) Automated evidence collection Assessment methodology implementation Reporting and dashboard functionality AI/ML platform integration Phase 3: Advanced Features (Months 7-9) Real-time monitoring and alerting Advanced analytics and risk scoring Regulatory compliance automation External framework integrations Phase 4: Enterprise Features (Months 10-12) Multi-tenant architecture Advanced workflow processes Enterprise security tool integration Advanced reporting and analytics Contributing This project is proprietary and not open source. For questions or collaboration inquiries, please contact the project owner.
License and Ownership © 2025 Darrell Mesa. All rights reserved.
Project Owner: Darrell Mesa (darrell.mesa@pm-ss.org)
IMPORTANT NOTICE: This software is proprietary and NOT FOR COMMERCIAL USE. This project is not open source and all rights are reserved by the owner. Unauthorized commercial use, distribution, or modification is strictly prohibited.
Usage Restrictions ✅ Educational and research purposes ✅ Internal organizational assessment and evaluation ✅ Non-commercial compliance and audit activities ❌ Commercial distribution or sale ❌ Integration into commercial products without explicit permission ❌ Modification for commercial purposes For commercial licensing inquiries, please contact: darrell.mesa@pm-ss.org
Support and Contact For technical support, questions, or collaboration opportunities:
Email: darrell.mesa@pm-ss.org Project Owner: Darrell Mesa Acknowledgments This toolkit is built upon the foundational work of:
ISACA: Artificial Intelligence Audit Toolkit (2024) NIST: AI Risk Management Framework for Generative AI (AI 600-1) Information Commissioner's Office (ICO) and The Alan Turing Institute: AI Explainability Framework Disclaimer This toolkit is provided for educational and assessment purposes. Users must verify all information and adapt the framework to their specific organizational requirements and regulatory environment. The project owner makes no warranties regarding the completeness or accuracy of compliance assessments performed using this toolkit.