This program is designed to prepare participants for the certification exam only.
The Certified Ethical Hacker v13 (AI) certification represents a globally recognized benchmark for professionals who analyze, detect, and secure against evolving cyber threats using structured hacking methodologies. It validates institutional knowledge of offensive and defensive cybersecurity aligned with international standards. The integration of artificial intelligence within this certification reflects the growing role of intelligent systems in shaping modern cyberattack strategies and defense frameworks. This training program provides structured coverage of ethical hacking concepts, threat models, and AI driven security mechanisms through theoretical and institutional perspectives. It focuses on strategic frameworks and analytical structures that support cybersecurity resilience in organizational environments.
Explore the ethical hacking lifecycle and the role of AI in offensive and defensive operations.
Classify the latest attack vectors across networks, applications, cloud, IoT, and AI/ML environments.
Analyze reconnaissance, exploitation, persistence, and evasion techniques using structured frameworks.
Evaluate theoretical models of malware behavior, cryptographic attacks, and institutional defense strategies.
Prepare for the certification exam.
Cybersecurity Managers.
Penetration Testing Leads.
Network and Cloud Security Administrators.
IT Risk and Compliance Officers.
Threat Intelligence and Forensic Analysts.
Ethical hacking lifecycle and adversary simulation structures.
AI applications in cybersecurity operations and governance.
Threat intelligence frameworks and attacker profiling models.
Penetration testing methodologies within institutional contexts.
Legal, ethical, and regulatory considerations in hacking strategies.
Structural differences between passive and active reconnaissance.
OSINT methodologies and AI-driven reconnaissance models.
Vulnerability assessment frameworks and theoretical scanning logic.
Exploitation lifecycle and privilege escalation structures.
Post exploitation, persistence, and evasion strategies in conceptual form.
Network traffic vulnerabilities and intrusion structures.
MITM, sniffing, and lateral movement as coordinated attack models.
Web, API, and application-layer attack surfaces.
Cloud security exposures including misconfiguration and identity exploitation.
IoT and OT systems as evolving strategic targets in modern environments.
Malware development, delivery structures, and institutional impacts.
Ransomware lifecycle and conceptual defense mechanisms.
Cryptographic weaknesses and theoretical password attack models.
Institutional defense mechanisms: IDS/IPS, firewalls, honeypots, anomaly detection.
AI enabled defense including predictive analytics and structured anomaly modeling.
Structural overview of the exam framework.
Reviewing key topics and concepts covered in the exam.
Sample exam questions and their potential answers.
Resources and materials for further study.