Tonex presents the Certified AI Penetration Tester – Blue Team™ (CAIPT-BT) Certification Course, a specialized program designed for professionals seeking expertise in safeguarding AI systems against cyber threats. This course focuses on the defensive aspects of AI penetration testing, equipping participants with the skills to proactively secure AI environments.
Learning Objectives:
- Develop advanced knowledge of AI penetration testing methodologies.
- Acquire skills to identify and mitigate vulnerabilities in AI systems.
- Explore defensive strategies for protecting AI models against cyber threats.
- Gain expertise in assessing and enhancing the security posture of AI applications.
- Foster the ability to conduct ethical and comprehensive AI penetration tests.
- Attain the CAIPT-BT certification, validating proficiency in AI blue teaming.
Audience: Designed for cybersecurity professionals, AI developers, and IT security specialists, the Certified AI Penetration Tester – Blue Team™ (CAIPT-BT) Certification Course is tailored for those responsible for securing AI systems against cyber threats. This course caters to individuals seeking to enhance their defensive capabilities in the context of AI penetration testing.
Course Outline:
Module 1: Advanced AI Penetration Testing Methodologies
- Overview of AI-Specific Penetration Testing Techniques
- Threat Modeling for AI Environments
- Exploitation of AI-Specific Vulnerabilities
- Advanced Social Engineering in AI Context
- Attack Surface Analysis for AI Systems
- Case Studies on Successful AI Penetration Tests
Module 2: Identifying and Mitigating Vulnerabilities in AI Systems
- Techniques for Identifying AI System Vulnerabilities
- Vulnerability Assessment in AI Models
- Patch Management Strategies for AI Systems
- AI-Specific Intrusion Detection and Prevention
- Secure Configuration Practices for AI Environments
- Continuous Monitoring for AI Security
Module 3: Defensive Strategies for Protecting AI Models
- Implementing Defensive Measures in AI Systems
- Secure Development Practices for AI Applications
- AI Model Hardening Techniques
- Securing AI Data Pipelines
- Implementing Secure Communication Protocols in AI
- Adaptive AI Security Controls
Module 4: Assessing and Enhancing Security Posture of AI Applications
- Security Assessment Frameworks for AI Applications
- Secure Deployment Practices for AI Models
- Securing AI APIs and Integrations
- Evaluating Third-Party AI Components
- Secure AI Model Lifecycle Management
- Case Studies on Improving AI Security Posture
Module 5: Ethical and Comprehensive AI Penetration Testing
- Ethical Considerations in AI Penetration Testing
- Legal and Regulatory Compliance in AI Security Testing
- AI-Specific Penetration Testing Reporting and Documentation
- Collaboration with Red Team for Holistic Testing
- Continuous Improvement in AI Security Testing
- Responsible Disclosure Practices in AI Security
Module 6: CAIPT-BT Certification Assessment
- Overview of the CAIPT-BT Certification Assessment
- Examination Format and Structure
- Strategies for Certification Preparation
- Mock Assessments and Feedback
- Successful Completion Criteria
- Awarding the Certified AI Penetration Tester – Blue Team™ (CAIPT-BT) Certification
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of AI Penetration Testing – Blue Team. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification:
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in AI Penetration Testing – Blue Team.
Exam Domains:
- Introduction to AI Security
- AI Vulnerability Assessment
- AI Threat Modeling
- AI Penetration Testing Methodologies
- AI Security Tools and Techniques
- AI Incident Response and Recovery
- AI Defense Strategies
- Ethical and Legal Considerations in AI Penetration Testing
Question Types:
- Multiple Choice
- True/False
- Fill in the Blank
- Matching
- Scenario-Based Questions
- Practical Simulations
Passing Criteria:
- Candidates must achieve a minimum score of 70% to pass the exam.
- Scores are calculated based on the overall performance across all domains.
- Practical simulations may have specific criteria for completion or success, as determined by the examiners.