Authors - Harsh Vardhan, Harsh Vikramaditya, Doyelshree Bhui, Shilpi Basak, Soumitra Sasmal, Subhajit Bhowmick, Ishan Ghosh Abstract - Security audits present a unique and ever evolving challenge due to the dynamic nature of cyberthreats and complex regulations. Traditional compliance audits remain largely manual and labor inten sive, resulting in vast inconsistencies. This paper introduces a solution to make compliance audits easier and faster by proposing a framework that leverages the use of Natural Language Processing and Large Lan guage Models to map organizational policies to frameworks and allows for real-time data from security controls to be validated against these complex security frameworks. Through a hybrid multi-model architec ture, the solutions in this paper aim to enhance the accuracy and trans parency of compliance evaluations coupled with evidence-backed insights. The results demonstrate the potential of integrating intelligent auditing systems to deliver compliance assessments that are consistent, accurate, and rapid; streamlining governance and improving cyber security posture management.
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