Course Overview
AI+ Ethical Hacker Practitioner™ equips cybersecurity professionals with practical skills to apply AI across ethical hacking, penetration testing, vulnerability management, threat hunting, SOC operations, and incident response. Through instructor-led learning, hands-on activities, and an end-to-end capstone, participants explore AI-assisted security testing, LLM and RAG security, adversarial AI, cloud and identity security, and governance to identify threats faster, strengthen defenses, and use AI responsibly in cybersecurity operations.
Who should attend
- IT Professional
- Security Analyst
Prerequisites
Required:
- Knowledge of Python, Java, C++,etc for automation and scripting.
- Understanding of networking protocols, subnetting, firewalls, and routing.
- Familiarity with fundamental cybersecurity concepts, including encryption, authentication, access controls, and security protocols.
- Proficiency in using Windows and Linux operating systems.
- Understanding of machine learning concepts, algorithms, and basic implementation.
- Understanding of web technologies, including HTTP/HTTPS protocols, and web servers.
Recommended: AI+ Everyone Fundamentals™ (AIEV) or AI+ Executive Fundamentals™ (AIE)
Course Objectives
- Explain core cybersecurity, ethical hacking, networking, Linux, and AI security fundamentals
- Apply AI to reconnaissance, enumeration, attack-surface mapping, and vulnerability analysis
- Understand AI-assisted web, API, password, cloud, container, and penetration testing techniques
- Identify security risks across LLMs, RAG systems, prompt injection, and AI agents
- Apply machine learning concepts to cybersecurity and adversarial AI scenarios
- Use AI to enhance threat hunting, detection engineering, SOC operations, and threat intelligence
- Apply AI-assisted approaches to incident response and digital forensic investigations
- Understand Zero Trust, IAM, PAM, non-human identity, cloud, and AI agent security controls
- Apply AI governance, risk, privacy, compliance, ethics, and responsible disclosure principles
- Integrate offensive and defensive security practices through an end-to-end AI-assisted ethical hacking engagement
Outline: AI+ Ethical Hacker Practitioner™ (AIEH)
1) Cybersecurity Ethical Hacking and AI Foundations
- Cybersecurity Fundamentals
- Ethical Hacking Fundamentals
- Core Security Frameworks
- AI in Cybersecurity
- Safe and Responsible AI Usage
2) Networking Linux Web Technologies and Reconnaissance Fundamentals
- Networking Fundamentals
- Linux Fundamentals for Ethical Hacking
- Web Application Fundamentals
- Reconnaissance Fundamentals
- AI-Assisted Reconnaissance
3) AIEnhanced Reconnaissance Enumeration and Attack Surface Mapping
- Reconnaissance Methodology
- Enumeration Fundamentals
- Cloud Reconnaissance
- API Reconnaissance
- AI for Attack Surface Mapping
4) Vulnerability Assessment and Risk Prioritization
- Vulnerability Assessment Basics
- Vulnerability Scanning
- Vulnerability Validation
- AI-Assisted Vulnerability Analysis
- Remediation Planning
5) AIAssisted Penetration Testing Web API Password Cloud and AI Application Security
- Penetration Testing Lifecycle
- Web Application Security
- API Security Testing Fundamentals
- Password Security
- Cloud and Container Pentesting Concepts
- AI in Penetration Testing
6) LLM RAG and AI Application Security
- LLM Application Architecture
- OWASP LLM Top 10
- Prompt Injection Fundamentals
- RAG Security (Retrieval-Augmented Generation)
- AI Agent Security
- Defensive Controls
7) Machine Learning for Cybersecurity and Adversarial AI
- Machine Learning Fundamentals
- Supervised Learning for Security
- Unsupervised Learning for Security
- Natural Language Processing (NLP) for Cybersecurity
- Adversarial Machine Learning
- Explainable AI (XAI)
8) Threat Hunting Detection Engineering and AIDriven SOC Operations
- Security Operations Center (SOC)
- Threat Hunting Fundamentals
- Detection Engineering
- AI in the Security Operations Center (SOC)
- Threat Intelligence
9) Incident Response Digital Forensics and AIAssisted Investigations
- Incident Response Lifecycle
- Incident Classification
- Evidence Handling
- Digital Forensics Basics
- AI-Assisted Incident Response
- AI-Specific Incident Response
10) Identity Security Zero Trust Cloud Security and NonHuman Identity
- Identity and Access Management (IAM) Basics
- Zero Trust Fundamentals
- Privileged Access Management (PAM)
- Non-Human Identity Security
- Cloud Security Fundamentals
- AI Agent Identity Controls
11) AI Governance Compliance Risk Management and Responsible Disclosure
- AI Governance Fundamentals
- NIST AI RMF and Generative AI Profile
- Privacy and Compliance
- AI Ethics
- Responsible Disclosure
- AI Security Reporting
12) Capstone Project EndtoEnd AIAssisted Ethical Hacking and Defense Engagement
- Scoping and Rules of Engagement
- Reconnaissance and OSINT
- Vulnerability Assessment
- AI-Assisted Penetration Testing
- LLM and AI Application Security Testing
- Detection Engineering and Threat Hunting
- Incident Response
- Governance and Reporting
13) Optional Module AI Agents for Ethical Hacking
- What Are AI Agents?
- Applications and Trends of AI Agents
- The Importance of AI Agents in Ethical Hacking
- How Does an AI Agent Work?
- Characteristics of AI Agents in Ethical Hacking
- Types of AI Agents