Certified AI Agent Security Analyst (CAA-SA) Certification Program by Tonex
Master the discipline of securing AI agents and multi-agent ecosystems with a program designed for real-world impact. You will learn how to anticipate advanced threats, harden agent architectures, and validate controls across the agent lifecycle. Cybersecurity for AI agents now determines the reliability of automated decision making and the resilience of enterprise workflows. Strong cybersecurity practices reduce model abuse, supply chain compromise, and cross-agent escalation that can disrupt critical operations.
This certification builds practical judgment through threat modeling, attack emulation, and control design aligned to industry frameworks. Graduates demonstrate assurance skills that translate directly into safer deployments, better incident outcomes, and confident stakeholder communication. The curriculum is compact, practitioner focused, and mapped to current standards, helping teams operationalize governance without slowing innovation. Join a focused cohort and transform agent security from a concern into a measurable competency that scales with your organization.
Learning Objectives
- Explain how cybersecurity shapes trustworthy AI agent behavior and reduces operational risk
- Build agent-centric threat models and abuse cases
- Detect and mitigate adversarial prompt injection and data leakage
- Assess multi-agent orchestration risks and escalation paths
- Map controls to OWASP LLM Top 10 and MITRE ATLAS techniques
- Design trust, authentication, authorization, and supply-chain safeguards
- Plan red team campaigns and translate findings into governance policy
Audience
- Cybersecurity Professionals
- AI security specialists
- Red teamers and offensive security practitioners
- SOC analysts and incident responders
- AI product owners and MLOps engineers
- Risk and compliance leaders
Course Modules
Module 1 — Threat Modeling Fundamentals
- Define agent assets and trust boundaries
- Identify attacker goals and capabilities
- Build STRIDE-inspired abuse cases
- Prioritize risks with likelihood impact
- Derive control requirements and tests
- Produce living threat model artifacts
Module 2 — Prompt Injection and Evasion
- Recognize injection and jailbreaking patterns
- Build guardrail and content policy checks
- Control tool use and function exposure
- Detect indirect injection via data sources
- Evaluate retrieval and output filtering
- Test evasion and bypass techniques
Module 3 — Multi-Agent Risks
- Map roles memory and messaging flows
- Analyze delegation and tool escalation
- Prevent privilege creep across agents
- Contain failures with sandboxing patterns
- Monitor cross-agent behavior signals
- Validate fallback and kill-switch design
Module 4 — OWASP LLM Top 10
- Align threats to A01–A10 categories
- Mitigate data leakage and exposure
- Harden plugin and tool integrations
- Secure prompt and secret management
- Enforce rate limiting and quotas
- Verify logging and auditability
Module 5 — MITRE ATLAS for Agents
- Navigate tactics techniques procedures
- Build detection rules for ATLAS events
- Map tests to coverage and gaps
- Correlate agent logs with SOC telemetry
- Craft adversary emulation plans
- Report assurance with ATT&CK-style cards
Module 6 — Trust AuthZ and Supply Chain
- Establish identity for agents and tools
- Apply authentication and delegated scopes
- Implement policy-based authorization
- Secure model and dataset provenance
- Vet third-party components and updates
- Continuously assess SBOM and risks
Exam Domains
- Threat Intelligence for Agent Systems
- Defensive Engineering Controls
- Offensive Testing and Red Teaming
- Governance and Risk Oversight
- Regulatory and Compliance Readiness
- Monitoring and Incident Response
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 Certified AI Agent Security Analyst CAA-SA. 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 Security Analyst CAA-SA.
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified AI Agent Security Analyst CAA-SA Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to secure your agent ecosystem Join the CAA-SA program by Tonex and become the specialist your organization trusts.