Don't Trust Your AI Agent (Until You Take This Course)
The security course every AI agent user needs. Learn threat modeling, Docker isolation, permission boundaries, skill vetting, monitoring, and prompt injection defense with real CVEs and attack data.
What You'll Learn
- Identify the documented attack vectors targeting AI agents using real CVE and research data
- Apply the OWASP Top 10 for Agentic Applications to build a threat model for any AI agent deployment
- Implement Docker isolation with 5 hardening flags that block the most common agent exploits
- Design permission boundaries using least privilege, scoped tokens, and credential isolation
- Evaluate third-party skills using a 5-point vetting framework before installation
- Build a monitoring setup that detects credential leaks, unauthorized tool calls, and anomalous agent behavior
- Explain why prompt injection succeeds against 85%+ of current defenses and apply layered mitigations
- Create a personal security policy that covers agent permissions, incident response, and weekly review
Course Syllabus
Prerequisites
- Basic familiarity with AI agents (chatbots, coding assistants, or tools like OpenClaw/Claude Code)
- Comfort using a terminal (command line basics)
- No security background required — we teach everything from scratch
Related Skills
Frequently Asked Questions
Do I need a security background?
No. This course teaches security concepts from scratch using real examples. If you can use a terminal and have interacted with an AI agent, you're ready.
Is this only about OpenClaw?
OpenClaw is our primary case study because it has the most documented security research. But every principle — threat modeling, isolation, permissions, monitoring — applies to Claude Code, Cursor, Windsurf, and any AI agent.
Will this course teach me to hack AI agents?
This is a defensive security course. You'll learn how attacks work so you can prevent them. We cover real attack data from security researchers, not attack tools.
I already use Docker. Do I still need Lesson 3?
Probably yes. AI agent containers need specific hardening flags (--cap-drop=ALL, --read-only, non-root user) that most Docker tutorials don't cover. Lesson 3 focuses on agent-specific isolation.