AI Red Teaming Training Syllabus & Modules
Complete dynamic pacing topics, hand-on tools, and project milestones.
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Detailed Syllabus
Below is the comprehensive, module-by-module curriculum. As this training is strictly 1-to-1, we can adjust the syllabus scope or spend more time on specific modules based on your learning speed.
Course Prerequisites
Basic computer operation and networking concepts (ports, IP addresses). No prior security background is required.
Full Curriculum Structure
Module 1: GenAI Security Foundations & LLM Architecture
3 Weeks- LLM API interfaces, system prompt structures, and token limits
- Linux commands, administration, and system configurations
- Direct and indirect prompt injection attack vectors
Module 2: Adversarial AI Probing & Vulnerability Audits
3 Weeks- Automated LLM vulnerability scanning with Microsoft PyRIT & NVIDIA Garak
- Exploiting security gaps in sandbox labs using NVIDIA Garak
- System privilege escalation and maintaining access vectors
Module 3: OWASP Top 10 for Large Language Models
3 Weeks- SQL Injection, Cross-Site Scripting (XSS), and CSRF attacks
- Testing AI agent tool calls, function execution, and permission escalation
- LLM input validation and NeMo Guardrail middleware configuration concepts
Module 4: GenAI Moderation & LLM Guardrail Engineering
3 Weeks- Building custom moderation middleware using NeMo Guardrails
- Setting up LLM prompt monitoring and guardrail rules rules
- Conducting vulnerability reviews on company staging systems
Tools & Technologies Mastered
You will gain hands-on operational capability in these tools during screenshare coding loops, creating real repositories.
Hands-on Lab Assignments & Projects
- Project 1: Penetration testing audit reports on local sandbox labs.
- Project 2: Configuring LLM guardrail policies and security groups in Linux.
- Project 3: Cryptographic hashing and key exchange scripts.
- Project 4: OWASP Web application vulnerability assessment project.
Syllabus FAQs
When does the next 1-to-1 training intake start?
Intakes start twice monthly on the 1st and 15th. The next upcoming 1-to-1 intake starts on October 1, 2026 (with secondary intake on October 15, 2026).
Is the AI Red Teaming syllabus updated for modern industry standards?
Yes. Our syllabus is continuously updated to cover the latest versions of Prompt Injection Analyzer, PyRIT, NVIDIA Garak, Burp Suite, LLM Moderation Middleware, NeMo Guardrails, Linux and modern production software engineering practices.
Can the syllabus be customized for my current skill level?
Because all sessions are strictly 1-to-1, your mentor can adjust module depth or accelerate topics based on your existing knowledge and target career goals.
Does the syllabus focus on theoretical concepts or hands-on coding?
Over 80% of training time is dedicated to live hands-on coding, terminal execution, pull request reviews, and building production applications.
Student Success Stories
Real feedback from students who completed our 1-to-1 virtual AI Red Teaming Training training.
"The AI Red Teaming lab at CACTS is outstanding. The 1-to-1 virtual session format allowed me to execute direct and indirect prompt injection attacks, bypass LLM guardrails like NeMo, and test OWASP Top 10 for LLM vulnerabilities on active staging applications."
Akash P.
AI Security Analyst, Kharadi, Pune"Learned offensive AI security, prompt injection payloads, and RAG data exfiltration defense in a practical 1-to-1 environment. My mentor demonstrated how to hijack multi-agent workflows and build custom moderation guardrails line-by-line."
Tanvi S.
LLM Security Researcher, Baner, Pune"I needed hands-on experience auditing GenAI applications and AI agents. We used Microsoft PyRIT and NVIDIA Garak to automate vulnerability scans and build defense middleware. The trainer's practical AI security experience was evident throughout."