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.
Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.
No learning outcomes available for this course.
Identify security weaknesses through authorized penetration testing and help organizations strengthen their cyber defenses.
Simulate real-world cyberattacks to uncover vulnerabilities in applications, networks, and systems before attackers do.
Assess systems for security vulnerabilities, prioritize risks, and recommend effective remediation strategies.
Monitor security events, analyze threats, and implement security measures to protect enterprise and AI-driven environments.
Evaluate web applications for security flaws and ensure they are resilient against common cyber threats and attacks.
Conduct adversarial security exercises to test organizational defenses and improve incident detection and response capabilities.
Assess AI models and AI-powered applications for security vulnerabilities, adversarial threats, and responsible AI implementation.
90 minutes
50 multiple-choice/multiple-response questions
| Foundation of Ethical Hacking Using Artificial Intelligence (AI): 5% | |
| Introduction to AI in Ethical Hacking: 9% | |
| AI Tools and Technologies in Ethical Hacking: 9% | |
| AI-Driven Reconnaissance Techniques: 9% | |
| AI in Vulnerability Assessment and Penetration Testing: 9% | |
| Machine Learning for Threat Analysis: 9% | |
| Behavioral Analysis and Anomaly Detection for System Hacking: 9% | |
| AI Enabled Incident Response Systems: 9% | |
| AI for Identity and Access Management (IAM): 9% | |
| Securing AI Systems: 9% | |
| Ethics in AI and Cybersecurity: 9% | |
| Capstone Project: 5% |
Acunetix
Wapiti
Nessus
OWASP ZAP
HackerGPT
Cobalt Strike
Shodan
Wazuh
Sumo Logic
YARA Rules