Certified AI Security Risk Management & Governance (CAISRMG) Certification Program by Tonex
The Certified AI Security Risk Management & Governance (CAISRMG) certification validates a professional’s ability to identify, assess, manage, and govern security risks across the AI lifecycle.
The program focuses on AI-specific threats, risk management frameworks, governance structures, regulatory compliance, and enterprise-scale oversight for AI systems.
This certification is designed to bridge cybersecurity, AI engineering, compliance, legal, and executive governance, ensuring that AI systems are secure, trustworthy, compliant, and auditable from design through deployment and operations.
Learning Objectives
By completing this certification, participants will be able to:
- Identify AI-specific security risks across the full AI lifecycle
- Apply structured AI risk management frameworks (e.g., NIST AI RMF, ISO/IEC 42001)
- Design AI governance structures, policies, and controls
- Assess risks related to data, models, pipelines, infrastructure, and AI supply chains
- Implement AI security controls and assurance mechanisms
- Align AI governance with regulatory, legal, and ethical obligations
- Conduct AI risk assessments, audits, and executive-level reporting
Target Audience
This certification is intended for:
- AI Security Architects and Engineers
- Cybersecurity and Risk Management Professionals
- AI Governance and Compliance Officers
- Chief AI Officers (CAIO), CISOs, CTOs
- AI Product Managers and Technical Leads
- Auditors and Assessors of AI Systems
- Legal, Policy, and Regulatory Professionals involved in AI oversight
Prerequisites
Recommended (not mandatory):
- Basic understanding of AI/ML concepts
- Familiarity with cybersecurity or risk management principles
- Experience in IT, engineering, compliance, or governance roles
Program Modules (Course Structure)
Module 1 – AI Systems & Risk Landscape
- AI system components and architectures
- AI lifecycle and risk introduction points
- Unique characteristics of AI risk vs traditional IT risk
Module 2 – AI Threats & Attack Vectors
- Data poisoning and data integrity risks
- Model theft, inversion, and extraction
- Prompt injection and indirect prompt attacks
- Adversarial ML attacks
- Supply-chain risks in AI models and datasets
- Insider and misuse risks
Module 3 – AI Security Risk Management Frameworks
- NIST AI Risk Management Framework (AI RMF)
- ISO/IEC 23894 (AI risk management)
- ISO/IEC 42001 (AI Management Systems)
- Mapping AI risk to enterprise risk management (ERM)
- Risk identification, analysis, evaluation, and treatment
Module 4 – AI Governance Models & Operating Structures
- AI governance operating models
- Roles and responsibilities (Board, CAIO, AI Risk Committee)
- Policies, standards, and decision authorities
- AI model approval and deployment governance
- Risk ownership and accountability
Module 5 – Secure AI Architecture & Controls
- Secure AI design principles
- Model security and protection techniques
- Data governance and protection controls
- Access control, authentication, and authorization for AI
- Monitoring, logging, and auditability
Module 6 – AI Assurance, Validation & Continuous Oversight
- AI risk assessments and threat modeling
- Red teaming and adversarial testing for AI
- Continuous risk monitoring and drift detection
- Incident response for AI security events
- Third-party and supplier risk management
Module 7 – Regulatory, Legal & Compliance Considerations
- AI-related laws and regulations (EU AI Act, U.S. frameworks, global trends)
- Privacy and data protection (GDPR, consent, data rights)
- Model transparency, explainability, and accountability
- Audit readiness and regulatory reporting
Module 8 – Enterprise AI Risk & Governance Case Studies
- AI risk register development
- Governance failure case studies
- Executive-level risk reporting and dashboards
- Board-level decision scenarios
Exam Structure
Exam Name: Certified AI Security Risk Management & Governance (CAISRMG) Exam
Format:
- 40 Multiple-Choice Questions
- Scenario-based and analytical questions included
Duration: 90 minutes
Delivery: Online
Passing Score: 70%
Exam Domains & Weights
Domain Topic Weight
Domain 1: AI Risk Landscape & Threats 15%
Domain 2: AI Security Risks & Attack Vectors 20%
Domain 3: AI Risk Management Frameworks 20%
Domain 4: AI Governance Structures & Policies 15%
Domain 5: Secure AI Architecture & Controls 15%
Domain 6: Compliance, Legal & Assurance 15%
Total 100%