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PenTest++: Elevating Ethical Hacking with AI and Automation

Haitham S. Al-Sinani, Chris J. Mitchell

TL;DR

The paper tackles the scalability and efficiency challenge of ethical hacking by introducing PenTest++, an AI-augmented, modular automation framework that blends GenAI guidance with human oversight across reconnaissance to reporting. It demonstrates a prototype in a Linux-based lab, integrating tools like nmap, gobuster, Hashcat, and Hydra with ChatGPT-based analytics to automate routine tasks and assist decision-making. The study highlights significant gains in workflow efficiency and structured reporting, while candidly addressing risks such as AI hallucinations, privacy concerns, and limited real-world generalizability. The work argues that mixed-initiative, AI-assisted penetration testing can augment cybersecurity professionals, and it outlines ethical safeguards and future directions to broaden applicability and enable quantitative evaluation.

Abstract

Traditional ethical hacking relies on skilled professionals and time-intensive command management, which limits its scalability and efficiency. To address these challenges, we introduce PenTest++, an AI-augmented system that integrates automation with generative AI (GenAI) to optimise ethical hacking workflows. Developed in a controlled virtual environment, PenTest++ streamlines critical penetration testing tasks, including reconnaissance, scanning, enumeration, exploitation, and documentation, while maintaining a modular and adaptable design. The system balances automation with human oversight, ensuring informed decision-making at key stages, and offers significant benefits such as enhanced efficiency, scalability, and adaptability. However, it also raises ethical considerations, including privacy concerns and the risks of AI-generated inaccuracies (hallucinations). This research underscores the potential of AI-driven systems like PenTest++ to complement human expertise in cybersecurity by automating routine tasks, enabling professionals to focus on strategic decision-making. By incorporating robust ethical safeguards and promoting ongoing refinement, PenTest++ demonstrates how AI can be responsibly harnessed to address operational and ethical challenges in the evolving cybersecurity landscape.

PenTest++: Elevating Ethical Hacking with AI and Automation

TL;DR

The paper tackles the scalability and efficiency challenge of ethical hacking by introducing PenTest++, an AI-augmented, modular automation framework that blends GenAI guidance with human oversight across reconnaissance to reporting. It demonstrates a prototype in a Linux-based lab, integrating tools like nmap, gobuster, Hashcat, and Hydra with ChatGPT-based analytics to automate routine tasks and assist decision-making. The study highlights significant gains in workflow efficiency and structured reporting, while candidly addressing risks such as AI hallucinations, privacy concerns, and limited real-world generalizability. The work argues that mixed-initiative, AI-assisted penetration testing can augment cybersecurity professionals, and it outlines ethical safeguards and future directions to broaden applicability and enable quantitative evaluation.

Abstract

Traditional ethical hacking relies on skilled professionals and time-intensive command management, which limits its scalability and efficiency. To address these challenges, we introduce PenTest++, an AI-augmented system that integrates automation with generative AI (GenAI) to optimise ethical hacking workflows. Developed in a controlled virtual environment, PenTest++ streamlines critical penetration testing tasks, including reconnaissance, scanning, enumeration, exploitation, and documentation, while maintaining a modular and adaptable design. The system balances automation with human oversight, ensuring informed decision-making at key stages, and offers significant benefits such as enhanced efficiency, scalability, and adaptability. However, it also raises ethical considerations, including privacy concerns and the risks of AI-generated inaccuracies (hallucinations). This research underscores the potential of AI-driven systems like PenTest++ to complement human expertise in cybersecurity by automating routine tasks, enabling professionals to focus on strategic decision-making. By incorporating robust ethical safeguards and promoting ongoing refinement, PenTest++ demonstrates how AI can be responsibly harnessed to address operational and ethical challenges in the evolving cybersecurity landscape.

Paper Structure

This paper contains 35 sections, 6 figures.

Table of Contents

  1. Introduction
  2. Research Problem, Hypotheses, and Contributions
  3. Problem Statement
  4. Research Questions
  5. Contribution to Knowledge
  6. GenAI and ChatGPT
  7. Laboratory Setup
  8. Development Language
  9. Physical Host and Virtual Environment Configuration
  10. GenAI Tool
  11. ChatGPT-PenTest++ Integration
  12. Methodology
  13. Prototype Implementation
  14. Reconnaissance Module
  15. Scanning & Enumeration Module
  16. ...and 20 more sections

Figures (6)

  • Figure 1: Host scanning
  • Figure 2: Port targets discovered
  • Figure 3: Password cracking
  • Figure 4: Shell payloads
  • Figure 5: Shell gained on target 192.168.1.7
  • ...and 1 more figures