Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S)

Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S) Certification Program by Tonex

Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S) Certification Program by Tonex prepares professionals to evaluate, challenge, and strengthen AI-enabled systems through structured offensive security methods. The program focuses on adversarial thinking, model abuse pathways, prompt manipulation risks, data poisoning concerns, and red teaming practices aligned with modern AI environments. Participants examine how attackers target AI pipelines, decision systems, APIs, integrations, and supporting infrastructure, then learn how to identify weaknesses before they become operational problems.

The program also highlights the growing cybersecurity importance of AI assurance across enterprise, defense, and critical infrastructure settings. As organizations adopt AI at scale, cybersecurity teams must understand how model behavior, data integrity, and automation can be exploited. Strong cybersecurity practices help reduce exposure to prompt injection, model evasion, unsafe outputs, privilege misuse, and trust failures in AI-driven operations. This certification supports professionals who need to connect offensive testing with practical cybersecurity controls, governance expectations, and resilient deployment strategies in high-risk environments.

Learning Objectives

• Understand the foundations of AI penetration testing and red teaming operations
• Identify attack surfaces across models, agents, APIs, data pipelines, and integrations
• Analyze adversarial techniques such as prompt injection, data poisoning, and model evasion
• Evaluate AI system weaknesses using structured offensive assessment methods
• Map findings to remediation strategies, governance needs, and operational risk reduction
• Apply red teaming practices to improve trust, resilience, and secure AI adoption
• Recognize how cybersecurity supports safer AI deployment, monitoring, and defensive response

Audience

• Penetration Testers
• Red Team Operators
• Security Engineers
• AI Security Analysts
• SOC and Threat Hunting Personnel
• Risk and Compliance Professionals
• Cybersecurity Professionals
• Technical Leaders Responsible for AI Assurance

Program Modules

Module 1: Foundations of AI Security Testing

• AI attack surface overview
• Threat models for AI
• Offensive testing principles
• Red teaming mission goals
• Risk drivers in AI
• Security testing workflows

Module 2: Prompt Injection and Model Abuse

• Prompt injection techniques
• Jailbreak pattern analysis
• Instruction override scenarios
• Unsafe output generation
• Misuse path identification
• Abuse case documentation

Module 3: Adversarial Attacks on AI Models

• Evasion attack concepts
• Poisoning attack methods
• Model extraction risks
• Inference manipulation tactics
• Robustness weakness analysis
• Attack success measurements

Module 4: AI Infrastructure and API Exploitation

• AI API attack vectors
• Authentication weakness review
• Plugin and tool abuse
• Data flow exposure
• Privilege escalation paths
• Integration security testing

Module 5: Red Team Operations for AI

• Campaign planning methods
• Objective driven scenarios
• Adversary emulation approaches
• Rules of engagement
• Evidence collection methods
• Reporting for stakeholders

Module 6: Defense Mapping and Risk Reduction

• Findings prioritization methods
• Control mapping strategies
• Detection improvement planning
• Governance alignment review
• Resilience validation methods
• Remediation communication practices

Exam Domains

1. AI Penetration Testing Principles
2. Adversarial Threat Analysis for AI Systems
3. Offensive Assessment of AI Applications
4. Secure AI Architecture Risk Evaluation
5. Governance, Reporting, and Remediation Strategy
6. Operational Integration of AI Security Testing

Course Delivery

The course is delivered through a combination of expert-led lectures, guided discussions, structured workshops, and applied project-based learning focused on AI penetration testing and red teaming. Participants gain access to curated resources, technical readings, scenario materials, case-based exercises, and practitioner insights that support deeper understanding of offensive AI security assessment techniques.

Assessment and Certification

Participants are assessed through quizzes, written assignments, scenario analysis, and a capstone-style evaluation focused on AI penetration testing and red teaming practices. Upon successful completion of the program, participants receive the Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S) credential from Tonex.

Question Types

• Multiple Choice Questions (MCQs)
• Scenario-based Questions

Passing Criteria

To pass the Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S) Certification Training exam, candidates must achieve a score of 70% or higher.

Advance your expertise in offensive AI security and strengthen your ability to assess real-world AI risk with the Certified AI Penetration Testing and Red Teaming Specialist (CAIPTRT-S) Certification Program by Tonex.