Certified Agentic Artificial Intelligence Red Team Professional (CAAIRTP) Certification Program by Tonex
The Certified Agentic Artificial Intelligence Red Team Professional (CAAIRTP) Certification Program by Tonex prepares professionals to evaluate, challenge, and strengthen autonomous and semi-autonomous Artificial Intelligence (AI) systems from an adversarial security perspective. Participants learn how agentic AI architectures operate, how agents use tools and memory, how multi-step reasoning can introduce attack paths, and how red team methodologies can uncover weaknesses before they are exploited in real environments.
The program uses a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in agentic AI security assessment projects. Participants examine threat modeling, prompt-based attacks, tool abuse, privilege escalation, memory manipulation, unsafe autonomy, model exploitation, and defensive validation.
Cybersecurity is central to agentic AI because autonomous systems may interact with sensitive data, applications, Application Programming Interfaces (APIs), and operational workflows. Effective cybersecurity testing helps organizations identify attack surfaces, validate safeguards, reduce unintended agent behavior, and improve the resilience of AI-enabled business and mission environments.
Learning Objectives
Upon successful completion of this program, participants will be able to:
- Explain core concepts, architectures, and operational patterns used in agentic Artificial Intelligence systems.
- Identify attack surfaces associated with autonomous agents, tools, memory, workflows, and external integrations.
- Perform structured threat modeling for agentic Artificial Intelligence environments.
- Evaluate prompt injection, tool misuse, privilege escalation, and agent manipulation risks.
- Assess multi-agent interaction risks, unsafe delegation, and trust boundary weaknesses.
- Design red team strategies for testing security controls and operational safeguards.
- Apply cybersecurity principles to strengthen agentic Artificial Intelligence systems against adversarial behavior and exploitation.
Audience
This certification program is designed for:
- Artificial Intelligence Security Professionals
- Artificial Intelligence Red Teamers
- Cybersecurity Professionals
- Penetration Testers
- Security Engineers
- Security Architects
- Artificial Intelligence Engineers
- Machine Learning Engineers
- Application Security Professionals
- Threat Modeling Specialists
- Security Operations Professionals
- Governance, Risk, and Compliance Professionals
- Technical Leaders responsible for Artificial Intelligence security
Program Modules
Module 1: Agentic AI Security Foundations and Threats
- Agentic Artificial Intelligence architecture fundamentals
- Autonomous and semi-autonomous agent behaviors
- Agent reasoning and decision pathways
- Tool and Application Programming Interface interactions
- Memory and context security risks
- Trust boundaries within agent workflows
- Common agentic Artificial Intelligence threat categories
Module 2: Adversarial Prompting and Agent Manipulation
- Direct and indirect prompt injection
- Instruction hierarchy manipulation techniques
- Context poisoning and malicious input
- Goal hijacking and task redirection
- System prompt exposure risks
- Agent response manipulation strategies
- Adversarial testing documentation practices
Module 3: Tool Abuse and Privilege Escalation
- Tool invocation security weaknesses
- Excessive permissions and authorization risks
- Application Programming Interface abuse scenarios
- Privilege escalation through agent actions
- Unauthorized data access pathways
- Unsafe command execution patterns
- Tool access validation and containment
Module 4: Memory Context and Multi-Agent Attacks
- Short-term and persistent memory risks
- Memory poisoning and manipulation methods
- Context leakage and information exposure
- Cross-agent trust and delegation weaknesses
- Multi-agent communication attack paths
- Identity and authorization challenges
- Agent collaboration security assessment
Module 5: Red Team Testing and Validation
- Agentic Artificial Intelligence red team planning
- Attack scenario development and prioritization
- Security test case design
- Control effectiveness validation
- Adversarial behavior observation methods
- Findings analysis and risk classification
- Red team reporting and remediation guidance
Module 6: Governance Resilience and Secure Operations
- Agentic Artificial Intelligence security governance
- Operational monitoring and anomaly detection
- Human oversight and intervention controls
- Incident response for agent failures
- Secure deployment and change management
- Cybersecurity assurance and control verification
- Continuous risk assessment and improvement
Exam Domains
- Agentic Artificial Intelligence Architecture and Risk
- Adversarial Prompting and Behavioral Exploitation
- Tool Access, Authorization, and Privilege Security
- Memory, Context, and Multi-Agent Risk
- Red Team Methodology and Security Validation
- Governance, Resilience, and Operational Assurance
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, practical exercises, case studies, and project-based learning facilitated by experts in Artificial Intelligence security and cybersecurity. Participants will have access to supporting learning resources, technical readings, assessment scenarios, security frameworks, and tools used for practical exercises.
The program follows a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in agentic Artificial Intelligence red team projects. Activities emphasize realistic security assessment workflows, attack scenario development, control validation, findings analysis, and professional security reporting.
Assessment and Certification
Participants will be assessed through quizzes, assignments, practical exercises, scenario-based activities, and a capstone project. Assessment activities measure understanding of agentic Artificial Intelligence security, adversarial techniques, threat modeling, tool abuse, memory risks, multi-agent vulnerabilities, red team methodologies, and cybersecurity controls.
Upon successful completion of the program requirements and certification examination, participants will receive the Certified Agentic Artificial Intelligence Red Team Professional (CAAIRTP) certification.
Question Types
- Multiple Choice Questions (MCQs)
- Scenario-Based Questions
Passing Criteria
To pass the Certified Agentic Artificial Intelligence Red Team Professional (CAAIRTP) Certification Training exam, candidates must achieve a score of 70% or higher.
Take the Next Step
Advance your expertise in adversarial Artificial Intelligence security with the Certified Agentic Artificial Intelligence Red Team Professional (CAAIRTP) Certification Program by Tonex. Develop the practical knowledge required to identify, test, document, and reduce vulnerabilities across autonomous agents, multi-agent environments, connected tools, and AI-enabled workflows.