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DOE OSTI · 3009426

Exploring Large Language Model Agents in Cybersecurity: A Literature Review with Experiments

Billingsley, Brett [Tennessee Technological Univ., Cookeville, TN (United States)]·Fassett, Jayden [Georgia State Univ., Atlanta, GA (United States)]·Werth, Aaron [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000319365627)·Singleton, Mathew [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0009000545881213)
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Abstract

The accelerated development and integration of large language model (LLM) agents have led researchers and developers to explore their effectiveness in cybersecurity, specifically with penetration testing (pentesting). Recent research efforts have attempted to use LLM agents to automate the process of pentesting because of the cost and time requirements that are required to perform a manual review. However, not all of the tools perform as expected. This paper reviews some of the newest and most popular autonomous pentesting frameworks, highlighting the capabilities and limitations of each one with the goal of providing the components needed to successfully and effectively build an autonomous pentesting agent in the future.

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97 MATHEMATICS AND COMPUTING

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Billingsley, Brett [Tennessee Technological Univ., Cookeville, TN (United States)], Fassett, Jayden [Georgia State Univ., Atlanta, GA (United States)], Werth, Aaron [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000319365627), Singleton, Mathew [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0009000545881213). 2025-12-01. Exploring Large Language Model Agents in Cybersecurity: A Literature Review with Experiments. https://doi.org/10.2172/3009426

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