Security Systems Assurance (SSA) is crucial as digital threats evolve and cybersecurity becomes more complex. Recent advancements in large language models (LLMs) have opened new avenues for enhancing SSA strategies. These models offer sophisticated data analysis and argumentation capabilities that were previously unattainable. Leveraging these capabilities, our paper introduces an innovative tool powered by LLMs that automates the generation of security assurance profiles by interpreting standards and security requirements specific to systems. We conducted a case study to compare the effectiveness of this LLM-powered tool against traditional methods managed by human experts. The results show that our automated tool’s performance closely matches that of human experts, highlighting the potential of LLMs to transform SSA processes and significantly improve the efficiency and reliability of cybersecurity defenses.