Official websites use. Share sensitive information only on official, secure websites. Conducting penetration testing pentesting in cybersecurity is a crucial turning point for identifying vulnerabilities within the framework of Information Technology IT , where real malicious offensive behavior is simulated to identify potential weaknesses and strengthen preventive controls.
Given the complexity of the tests, time constraints, and the specialized level of expertise required for pentesting, analysis and exploitation tools are commonly used. Although useful, these tools often introduce uncertainty in findings, resulting in high rates of false positives. To enhance the effectiveness of these tests, Machine Learning ML has been integrated, showing significant potential for identifying anomalies across various security areas through detailed detection of underlying malicious patterns.
However, pentesting environments are unpredictable and intricate, requiring analysts to make extensive efforts to understand, explore, and exploit them. This study considers these challenges, proposing a recommendation system based on a context-rich, vocabulary-aware transformer capable of processing questions related to the target environment and offering responses based on necessary pentest batteries evaluated by a Reinforcement Learning RL estimator.
This RL component assesses optimal attack strategies based on previously learned data and dynamically explores additional attack vectors. The system achieved an F1 score and an Exact Match rate over With the continuous advancement of technology, cybersecurity has become crucial for protecting digital assets against threats, vulnerabilities, malicious artifacts, and other sophisticated cyber risks that impact their environment [ 1 ]. In this context, underpinned by the principles of Confidentiality, Integrity, and Availability CIA , offensive cybersecurity is proposed as a range of dynamic techniques to robustly assess whether the applied controls and policies are effectively maintained within the targeted infrastructure [ 2 ].
Through the execution of tests that simulate active attacks, mimicking the real behavior of a malicious actor, vulnerabilities in various information assets can be assessed, either manually or automatically. This process ultimately facilitates the identification of the most effective defense-response strategies. While various methodologies and techniques for pentesting exist, the SysAdmin, Audit, Networking, and Security SANS Institute [ 4 ] has articulated a set of refined steps to conduct a comprehensive audit.
