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Maximizing Penetration Testing Success with Effective Reconnaissance Techniques Using ChatGPT

EasyChair Preprint no. 12396

11 pagesDate: March 5, 2024


The study investigates the integration of ChatGPT, a generative pretrained transformer language model into the reconnaissance phase of penetration testing and enhance the efficiency and depth of information gathering during critical security assessments offering potential improvements to traditional approaches. The research study addresses the challenge of optimizing the reconnaissance phase in penetration testing. It seeks to provide a solution by exploring the capabilities of ChatGPT in extracting valuable data, such as various aspects of the digital footprint or infrastructure of a system or an organization. The scope of the research relies in demonstrating how ChatGPT can contribute to the planning phase of penetration testing, guiding the selection of tactics, tools, and techniques for identifying and mitigating potential risks that could be used to assist with securing Internet accessible assets of a system or an organization. The research adopts a case study methodology to assess the effectiveness of ChatGPT in reconnaissance. Tailored questions are formulated to extract specific information relevant to penetration testing. The study highlights the importance of prompt engineering emphasizing the need for carefully constructed questions to ensure usable results. The research showcases the ability of ChatGPT to provide diverse and insightful reconnaissance information. The research study extends to the broader field of cybersecurity where artificial intelligence language models can play a valuable role in enhancing the success of reconnaissance in penetration testing. The research suggests that integrating ChatGPT into penetration testing can bring about positive changes in the efficiency and depth of information obtained during reconnaissance. The results of the study determine that incorporating ChatGPT in the reconnaissance phase significantly benefits penetration testers by offering valuable insights and streamlining subsequent assessment planning.

Keyphrases: Artificial Intelligence, ChatGPT, Cybersecurity, penetration testing, Reconnaissance

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Sheetal Temara},
  title = {Maximizing Penetration Testing Success with Effective Reconnaissance Techniques Using ChatGPT},
  howpublished = {EasyChair Preprint no. 12396},

  year = {EasyChair, 2024}}
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