AI-based privilege escalation detection focuses on identifying excessive permissions, unauthorized access opportunities, and suspicious activities that may allow users to gain privileges beyond their intended access levels in Linux environments. It involves analyzing file-system access-control policies, permission configurations, sudo usage patterns, and security logs to identify potential privilege misuse and abnormal administrative activities. By combining LLM-based security policy analysis with machine learning classification, this approach helps identify risky permission settings, recognize suspicious privilege-related behavior, and distinguish potentially malicious activities from legitimate system administration. The resulting findings support early detection of privilege escalation risks, improved access-control enforcement, and timely implementation of corrective security measures to protect system resources and prevent unauthorized administrative access.