Opleiding: AI+ Ethical Hacker Practitioner™

Protect Digital Landscapes: Harness AI-Enhanced Technologies

The AI+ Ethical Hacker Practitioner™ certification validates knowledge of the intersection of cybersecurity and artificial intelligence, a pivotal juncture in an era of rapid technological progress. Designed for cybersecurity professionals and ethical hacking practitioners, it assesses comprehensive knowledge of AI’s impact on digital offense and defense strategies. Unlike conventional ethical hacking certifications, this certification validates competency in applying AI techniques to enhance cybersecurity approaches. It is intended for professionals seeking to validate expertise in the integration of advanced AI methods with ethical hacking practices in a rapidly evolving digital landscape.

Cybersecurity Professionals: Those looking to enhance their skills in proactive defense and AI-driven threat detection. 

Ethical Hackers: Individuals focused on mastering advanced hacking techniques and staying ahead of emerging cybersecurity threats. 

Technology Leaders and Decision Makers: Executives and managers aiming to understand how AI and ethical hacking can secure their organizations. 

Aspiring Students: Learners interested in building a career in cybersecurity, gaining foundational knowledge and practical skills in ethical hacking. 

• Stay Ahead of Technological AdvancementsValidates capability in AI is transforming cybersecurity, enabling you to stay at the forefront of evolving threats.
• Bridge the Gap Between AI and CybersecurityValidates competency in combining AI techniques with ethical hacking to improve digital defense strategies.
• Boost Career OpportunitiesExam includes scenario-based evaluation of AI-driven security methods, validating competency in addressing real-world cyber threats.
• Future-Proof Your SkillsValidates expertise in AI-powered ethical hacking, positioning you as an expert in a rapidly advancing digital landscape.

• 1.1 Cybersecurity Fundamentals
• 1.2 Ethical Hacking Fundamentals
• 1.3 Core Security Frameworks
• 1.4 AI in Cybersecurity
• 1.5 Safe and Responsible AI Usage

• 2.1 Networking Fundamentals
• 2.2 Linux Fundamentals for Ethical Hacking
• 2.3 Web Application Fundamentals
• 2.4 Reconnaissance Fundamentals
• 2.5 AI-Assisted Reconnaissance

• 3.1 Reconnaissance Methodology
• 3.2 Enumeration Fundamentals
• 3.3 Cloud Reconnaissance
• 3.4 API Reconnaissance
• 3.5 AI for Attack Surface Mapping

• 4.1 Vulnerability Assessment Basics
• 4.2 Vulnerability Scanning
• 4.3 Vulnerability Validation
• 4.4 AI-Assisted Vulnerability Analysis
• 4.5 Remediation Planning

• 5.1 Penetration Testing Lifecycle
• 5.2 Web Application Security
• 5.3 API Security Testing Fundamentals
• 5.4 Password Security
• 5.5 Cloud and Container Pentesting Concepts
• 5.6 AI in Penetration Testing

• 6.1 LLM Application Architecture
• 6.2 OWASP LLM Top 10
• 6.3 Prompt Injection Fundamentals
• 6.4 RAG Security (Retrieval-Augmented Generation)
• 6.5 AI Agent Security
• 6.6 Defensive Controls

• 7.1 Machine Learning Fundamentals
• 7.2 Supervised Learning for Security
• 7.3 Unsupervised Learning for Security
• 7.4 Natural Language Processing (NLP) for Cybersecurity
• 7.5 Adversarial Machine Learning
• 7.6 Explainable AI (XAI)

• 8.1 Security Operations Center (SOC)
• 8.2 Threat Hunting Fundamentals
• 8.3 Detection Engineering
• 8.4 AI in the Security Operations Center (SOC)
• 8.5 Threat Intelligence

• 9.1 Incident Response Lifecycle
• 9.2 Incident Classification
• 9.3 Evidence Handling
• 9.4 Digital Forensics Basics
• 9.5 AI-Assisted Incident Response
• 9.6 AI-Specific Incident Response

• 10.1 Identity and Access Management (IAM) Basics
• 10.2 Zero Trust Fundamentals
• 10.3 Privileged Access Management (PAM)
• 10.4 Non-Human Identity Security
• 10.5 Cloud Security Fundamentals
• 10.6 AI Agent Identity Controls

• 11.1 AI Governance Fundamentals
• 11.2 NIST AI RMF and Generative AI Profile
• 11.3 Privacy and Compliance
• 11.4 AI Ethics
• 11.5 Responsible Disclosure
• 11.6 AI Security Reporting

• 12.1 Scoping and Rules of Engagement
• 12.2 Reconnaissance and OSINT
• 12.3 Vulnerability Assessment
• 12.4 AI-Assisted Penetration Testing
• 12.5 LLM and AI Application Security Testing
• 12.6 Detection Engineering and Threat Hunting
• 12.7 Incident Response
• 12.8 Governance and Reporting

• 1.1 What Are AI Agents?
• 1.2 Applications and Trends of AI Agents
• 1.3 The Importance of AI Agents in Ethical Hacking
• 1.4 How Does an AI Agent Work?
• 1.5 Characteristics of AI Agents in Ethical Hacking
• 1.6 Types of AI Agents

• Acunetix
• Wapiti
• Nessus
• OWASP ZAP
• HackerGPT
• Cobalt Strike
• Shodan
• Wazuh
• Sumo Logic
• YARA Rules

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

De OCICT maatwerk-methode houdt in dat op basis van de behoefte van de klant - en indien nodig na een intakegesprek - een individueel opleidingstraject wordt opgesteld. De trainingen worden veelal individueel gevolgd, zodat iedere training een maatwerktraject is. Klassikale trainingen zijn natuurlijk mogelijk, mits ze aansluiten bij de leerbehoeften van de deelnemers / opdrachtgever.

Alle onderdelen van de training kennen een voortdurende wisselwerking tussen theorie en praktijk. De inhoud van de training kan vooraf per cursist worden aangepast en tijdens de cursus worden bijgesteld. De focus ligt op maatwerk: het traject wordt afgestemd op de doelstellingen van de deelnemer(s) en/of opdrachtgever, ongeacht of het individueel of klassikaal wordt aangeboden.