Certified Agentic AI Security Professional
A 3-day, hands-on certification covering the attack and defence of autonomous AI agents, LLM systems and Model Context Protocol (MCP) architectures — culminating in a live Red Team vs Blue Team capstone.
Attack and defend the next generation of autonomous AI.
Enterprises are moving from chat-based LLMs to autonomous agents that plan, act, use tools, persist memory and coordinate across MCP architectures. The attack surface has shifted with them — reflection loops, tool invocation, vector stores and inter-agent trust now form a kill chain that traditional security tooling does not cover.
The Axiom Prime Certified Agentic AI Security Professional course equips engineers and red teamers to map that attack surface, execute the full adversarial kill chain against live agents, and engineer the defensive controls, observability and governance required to ship agentic AI safely in production.
Built around MITRE ATLAS, OWASP LLM Top 10, NIST AI RMF and ISO/IEC 42001 — and delivered through 14+ hands-on labs and a Red Team vs Blue Team capstone on an enterprise HR multi-agent system.
What you'll learn
- Map the complete attack surface of agentic AI deployments — from LLM reasoning loops to MCP architectures and multi-agent orchestration.
- Execute red-team operations against autonomous agent systems using prompt injection, tool abuse, memory poisoning and recursive chaining.
- Engineer defensive controls — Zero Trust agent identity, secure RAG, HITL approval workflows and kill-switch mechanisms.
- Operate observability and detection pipelines using LangSmith, OpenTelemetry and SIEM integrations for AI-specific incident response.
After certification you'll be able to
- Build STRIDE-based threat models and full adversarial kill chains for enterprise multi-agent architectures.
- Execute prompt injection, tool abuse, memory poisoning and recursive chaining attacks against live agents.
- Implement Zero Trust controls, scoped permissions and HITL approval workflows for autonomous AI.
- Deploy LangSmith + OpenTelemetry observability and configure SIEM detection rules for AI attack indicators.
- Design and test kill-switch mechanisms that safely suspend compromised agents with forensic state preservation.
- Apply NIST AI RMF and ISO 42001 governance requirements to produce pre-production security evidence.
Three days. 24 hours. One enterprise capstone.
Foundations of Agentic AI & Attack Surface
- ›Evolution from LLMs to Agentic AI
- ›MCP Fundamentals & Security
- ›Agentic AI Attack Surface — 8 primary vectors
- ›Prompt Injection & Tool Abuse — Deep Dive
Agentic AI Red Teaming & Adversarial Attacks
- ›AI Red Team Methodology & Threat Modelling (STRIDE, MITRE ATLAS)
- ›Advanced Adversarial Attack Techniques
- ›Multi-Agent & MCP Attack Chains
- ›Full Autonomous Kill Chain Construction
Defensive AI Engineering, Governance & Monitoring
- ›Zero Trust Architecture for AI Agents
- ›Secure Memory & RAG Architecture
- ›HITL Controls, Kill-Switch & Governance
- ›Agent Telemetry, Observability & Detection
- ›AI Governance & Secure SDLC
- ›Capstone — Red Team vs Blue Team Exercise
14+ Hands-On Labs & Capstone
From memory poisoning a ChromaDB store to building a HITL approval workflow and configuring threshold-based kill switches — every module pairs theory with labs. Day 3 closes with a 3-hour Red Team vs Blue Team capstone on an enterprise HR multi-agent deployment.
Certification Exam
- 2-hour hands-on practical exam
- 70% passing score
- Aligned with MITRE ATLAS & NIST AI RMF
- 3-day intensive program
Production frameworks. Real adversarial tooling.
Built for AI security engineers and red teamers.
Pre-requisites: Working knowledge of LLM applications, Python, and cybersecurity fundamentals. Prior exposure to LangChain or another agent framework is beneficial.
Ready to secure autonomous AI in production?
Reserve your seat in the next CAAISP cohort, or talk to us about private on-site delivery for your team.