Upcoming dates

All times shown in the class's own timezone.

Dates	Starts	Where	Status	Seat	Book
Sep 28 to Oct 2	9:00 AM to 5:00 PM EDT	Live virtual	SCHEDULED	$2,995

About this class

A hands-on, 5-day advanced certification for penetration testers and red teamers on attacking and securing AI systems, from prompt injection and adversarial ML to training-pipeline and supply-chain attacks, culminating in a capstone red team engagement.

Course outline

Module 01: Offensive AI and AI System Hacking Methodology

AI & ML Fundamentals
AI Attack Surface and Threat Landscape (ATLAS-Aligned)
AI Attack Taxonomy and Classification
OWASP LLM and ML Top 10 (2025), Overview & Mapping
AI System Hacking Methodology
Securing AI Systems, Foundations (Defensive Anchor)
AI Security Governance and Compliance

Module 02: AI Reconnaissance and Attack Surface Mapping

OSINT for AI Assets
Tools and Techniques for AI OSINT
Data & Training Pipeline Intel Gathering
Mapping AI Attack Surfaces from OSINT
Discovering AI Endpoints & Services
AI API & Parameter Enumeration
Model & Vector Store Enumeration
Defensive, Reducing AI OSINT Exposure
Defensive, Hardening Enumerated Surfaces
AI Threat Intelligence & Continuous Monitoring

Module 03: AI-Specific Vulnerability Scanning and Fuzzing

Fundamentals of AI Vulnerability Assessment
Tools and Techniques for Vulnerability Scanning
Fuzzing Techniques for AI Systems
Defensive, Integrating Scanning & Fuzzing

Module 04: Prompt-Based and LLM Application Attacks

LLM Architecture & Trust Boundaries
Prompt Injection & Jailbreaking
Sensitive Information Disclosure and System Prompt Leakage
Improper Output Handling and Misinformation
Advanced Prompt Attack Techniques
Defensive, Secure LLM Application Design

Module 05: Adversarial Machine Learning and Model Privacy Attacks

Adversarial ML Attacks
Practical Adversarial Input Attacks
Privacy & Model Extraction Attacks
Evaluating Robustness & Trustworthiness
Emerging Model Attack Techniques
Defensive, Privacy & Robustness Mitigations

Module 06: Data and Training Pipeline Attacks

Understanding AI Data & Training Pipelines
Data Poisoning Attacks
Backdoor / Trojan Attacks in Training Pipelines
AI Supply Chain Attack Vectors
Defensive, Securing Data & Training Pipelines

Module 07: Agentic AI and Model-to-Model Attacks

Agentic AI Architecture & Attack Surface
Excessive Agency & Autonomy
Model-to-Model and Cross-LLM Attacks
Unbounded Consumption and Denial of Wallet
AI Workflow and Orchestration Attacks
Defensive, Securing Agentic Applications

Module 08: AI Infrastructure and Supply Chain Attacks

AI Infrastructure & Integration Landscape
System and Framework Exploits
Tool and API Abuse in AI Apps
Supply Chain Threats (Deep Dive)
Defensive, Hardening AI Infra & Supply Chain

Module 09: AI Security Testing, Evaluation, and Hardening

AI Security Test & Evaluation Fundamentals
Designing AI Security Test Plans
Executing AI Security Tests
Reporting, Assurance & Risk Management
Defensive, Embedding T&E into MLOps/DevSecOps

Module 10: AI Incident Response, Forensics, and Capstone Red Team

Detecting & Responding to AI-Specific Incidents
Logging, Telemetry & Evidence Collection
AI Forensics & Post-Incident Analysis
Capstone: Full-Scope AI Red Team Engagement
Course Wrap-Up & Professional Practice

Before you attend

Strong technical background recommended, Requires: 2-3 years of cybersecurity experience, with understanding of security operations, networks or application security and offensive security experience

Who this is for

Penetration Testers / Ethical Hackers, Red Team / Offensive Security Specialists, Security Engineers / DevSecOps Engineers, SOC Analysts / Incident Responders, AI/ML Engineers focused on security