Revised 8/2026

ITN 295 - Applied Artificial Intelligence for Ethical Hacking (3 CR.)

Course Description

This course introduces students to the use of Artificial Intelligence and AI agents in ethical hacking and vulnerability assessment. Students learn how AI technologies such as large language models, AI agents, and automated security tools can assist penetration testers in identifying vulnerabilities, analyzing attack surfaces, automating repetitive tasks, and generating security recommendations. Students will work in controlled lab environments to perform reconnaissance, vulnerability scanning, web application testing, and reporting using AI-assisted workflows while adhering to legal and ethical standards. 

General Course Purpose

The purpose of this course is to equip students with a foundation in applying AI techniques to secure digital systems and enhance security operations. Students learn to protect AI-driven infrastructures, automate detection and response processes, and ensure compliance with ethical and regulatory frameworks. The course prepares learners for careers in AI-augmented cybersecurity and security operations centers (SOCs).

Course Prerequisites/Corequisites

Recommended:
ITN 260 - Network Security Basics
ITN170 - Linux administration

Course Objectives

Upon completing the course, the student will be able to: 

  • Explain AI concepts relevant to cybersecurity and penetration testing
  • Configure AI tools and local LLM environments
  • Use AI assistants to automate reconnaissance activities
  • Perform vulnerability assessments using AI-assisted workflows
  • Analyze vulnerability scan results
  • Identify false positives generated by AI systems
  • Use AI agents to assist with web application testing
  • Evaluate ethical and legal implications of AI in cybersecurity
  • Generate professional penetration testing reports using AI assistance
  • Develop AI workflows for cybersecurity tasks

Student Learning Outcomes

  • Explain how AI models, data, and automation enhance cybersecurity operations.
  • Identify and mitigate threats targeting AI systems and model integrity.
  • Configure and manage secure AI deployment environments across varied infrastructures.
  • Use AI-driven tools to improve detection accuracy and incident response efficiency.
  • Evaluate adversarial risks and apply appropriate countermeasures to protect AI assets.
  • Incorporate governance and compliance practices to ensure responsible and ethical AI security adoption.
  • Demonstrate readiness for the CompTIA SecAI+ certification exam.