Certified AI Agent Red Team Professional (CAART) Certification Program by Tonex
CAART is a rigorous program that prepares professionals to probe, pressure, and harden AI agents across complex ecosystems. You will learn how adversaries induce misalignment, bypass controls, and pivot through agent-to-agent workflows while preserving safety and ethics.
Cybersecurity impact is immediate as organizations confront AI driven threat surfaces that evolve faster than traditional defenses. Cybersecurity readiness improves when teams can anticipate adversarial prompts, data poisoning, and tool misuse before production exposure.
Cybersecurity leadership benefits from repeatable playbooks that translate red team findings into resilient architectures and accountable governance.
Graduates leave with practical tactics, precise methodology, and reporting skills that drive measurable risk reduction and executive confidence.
Learning Objectives
- Map multi-agent threat surfaces and prioritize exploitable paths
- Craft and contain jailbreaks while documenting reproducible procedures
- Exploit memory, context, and goal models to reveal systemic weaknesses
- Evaluate and attack agentic toolchains, APIs, and plug-ins safely
- Translate findings into blue team detections and architectural safeguards
- Strengthen cybersecurity posture by converting adversarial insights into policy and controls
Audience
- AI Red Teamers
- Penetration Testers
- Cybersecurity Professionals
- Security Architects and Engineers
- Threat Intelligence Analysts
- AI Researchers and Developers
Course Modules
Module 1: Red-Team Ecosystems
- Scoping multi-agent terrains
- Attack surface enumeration
- Trust boundaries and roles
- Chain-of-thought exposure risks
- Prioritization and hypothesis design
- Ethics and guardrail alignment
Module 2: Jailbreak Tactics
- Prompt attack taxonomies
- Role hijacking and persona flips
- Safety bypass chaining
- Cognitive overload patterns
- Recovery and containment cues
- Reporting reproducibility steps
Module 3: Memory & Context Abuse
- Session and long-term memory abuse
- Retrieval manipulation methods
- Context window poisoning
- Tool-choice nudging attacks
- Conversation stitching exploits
- Mitigation through scoping
Module 4: Goal & Planning Attacks
- Objective inversion strategies
- Plan interference tactics
- Reward hacking scenarios
- Delegation abuse pathways
- Autonomy throttling checks
- Safe rollback procedures
Module 5: API and Plug-in Threats
- Tool invocation profiling
- Input and output tampering
- OAuth and token exposure
- Supply chain dependency risks
- Rate and quota evasion
- Secure wrapper patterns
Module 6: Blue Team Countermoves
- Detection engineering for agents
- Guardrail tuning workflows
- Memory hygiene playbooks
- Policy to control mapping
- Post-incident hardening steps
- Metrics and success criteria
Exam Domains
- Threat Modeling for Agents
- Adversarial Prompt Engineering
- Data Integrity and Exposure
- Incident Response for AI
- Governance and Risk Management
- Evidence Handling and Reporting
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, guided exercises, and project-based learning, facilitated by experts in the field of Certified AI Agent Red Team Professional CAART. 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 Certified AI Agent Red Team Professional CAART.
Question Types
- Multiple Choice Questions MCQs
- Scenario-based Questions
Passing Criteria
To pass the Certified AI Agent Red Team Professional CAART Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to pressure-test your AI defenses and lead with confidence Join CAART by Tonex today and become the adversary your cybersecurity program needs.