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Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

Created by
  • Haebom

Author

Antonio L opez Mart inez, Alejandro Cano, Antonio Ruiz-Mart inez

Outline

This paper evaluates the effectiveness of penetration testing (pentesting) using generative artificial intelligence (GenAI) tools (Claude Opus, GPT-4, Copilot). Experiments were conducted in a virtual environment across each stage of the Penetration Testing Execution Standard (PTES). While GenAI tools cannot automate the entire pentest process, they significantly improve the efficiency and effectiveness of specific tasks. Claude Opus, in particular, outperformed other tools.

Takeaways, Limitations

Takeaways:
We empirically demonstrate that GenAI tools can efficiently support the pentesting process.
Confirm the excellence of a specific GenAI tool (Claude Opus) and contribute to establishing future tool selection and utilization strategies.
Proposing a plan to utilize GenAI to improve and automate the pentest process.
Limitations:
Limited GenAI tools and experimental environments make generalization difficult.
Complete pentest automation of GenAI tools is not yet possible.
There is a possibility that unexpected problems may occur when applied in a real environment.
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