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AI+ Ethical Hacker Practitioner™
USD$495.00 (GST excl.)
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.
Duration
Instructor-Led: 5 days (live or virtual)
Self-Paced: 40 hours of content
Self-Paced: 40 hours of content
Format
Online, self-paced
Exam
50 questions, 70% passing, 90 minutes, online proctored exam
Overview
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.
Prerequisites
Programming, networking, cybersecurity, operating systems, ML fundamentals, and web technologies knowledge.
What you’ll learn
- 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.
Why this certification matters
- Stay Ahead of Technological Advancements Validates capability in AI is transforming cybersecurity, enabling you to stay at the forefront of evolving threats.
- Bridge the Gap Between AI and Cybersecurity Validates competency in combining AI techniques with ethical hacking to improve digital defense strategies.
- Boost Career Opportunities Exam includes scenario-based evaluation of AI-driven security methods, validating competency in addressing real-world cyber threats.
- Future-Proof Your Skills Validates expertise in AI-powered ethical hacking, positioning you as an expert in a rapidly advancing digital landscape.
Tools you’ll use
Acunetix
Wapiti
Nessus
OWASP ZAP
HackerGPT
Cobalt Strike
Shodan
Wazuh
Sumo Logic
YARA Rules
Learning Modules
13 modules
1Module 1: Cybersecurity, Ethical Hacking, and AI Foundations
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
1.2 Ethical Hacking Fundamentals
1.3 Core Security Frameworks
1.4 AI in Cybersecurity
1.5 Safe and Responsible AI Usage
2Module 2: Networking, Linux, Web Technologies, and Reconnaissance Fundamentals
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
2.2 Linux Fundamentals for Ethical Hacking
2.3 Web Application Fundamentals
2.4 Reconnaissance Fundamentals
2.5 AI-Assisted Reconnaissance
3Module 3: AI-Enhanced Reconnaissance, Enumeration, and Attack Surface Mapping
3.1 Reconnaissance Methodology
3.2 Enumeration Fundamentals
3.3 Cloud Reconnaissance
3.4 API Reconnaissance
3.5 AI for Attack Surface Mapping
3.2 Enumeration Fundamentals
3.3 Cloud Reconnaissance
3.4 API Reconnaissance
3.5 AI for Attack Surface Mapping
4Module 4: Vulnerability Assessment and Risk Prioritization
4.1 Vulnerability Assessment Basics
4.2 Vulnerability Scanning
4.3 Vulnerability Validation
4.4 AI-Assisted Vulnerability Analysis
4.5 Remediation Planning
4.2 Vulnerability Scanning
4.3 Vulnerability Validation
4.4 AI-Assisted Vulnerability Analysis
4.5 Remediation Planning
5Module 5: AI-Assisted Penetration Testing: Web, API, Password, Cloud, and AI Application Security
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
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
6Module 6: LLM, RAG, and AI Application Security
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
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
7Module 7: Machine Learning for Cybersecurity and Adversarial AI
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)
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)
8Module 8: Threat Hunting, Detection Engineering, and AI-Driven SOC Operations
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
8.2 Threat Hunting Fundamentals
8.3 Detection Engineering
8.4 AI in the Security Operations Center (SOC)
8.5 Threat Intelligence
9Module 9: Incident Response, Digital Forensics, and AI-Assisted Investigations
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
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
10Module 10: Identity Security, Zero Trust, Cloud Security, and Non-Human Identity
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
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
11Module 11: AI Governance, Compliance, Risk Management, and Responsible Disclosure
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
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
12Module 12: Capstone Project – End-to-End AI-Assisted Ethical Hacking and Defense Engagement
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
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
13Optional Module: AI Agents for Ethical Hacking
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
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
| Format | Online, self-paced |
|---|---|
| Duration | Instructor-Led: 5 days (live or virtual) |
| Exam | 50 questions, 70% passing, 90 minutes, online proctored exam |
| Included | Instructor-led OR Self-paced course + Official exam + Digital badge |
| Prerequisites | Programming, networking, cybersecurity, operating systems, ML fundamentals, and web technologies knowledge. |
| Delivery | Projects & case studies |
| Outcome | Industry-recognized credential + hands-on experience |
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