AI-based security log analysis focuses on examining and correlating system and web server logs to identify suspicious activities, recognize multi-stage cyberattack patterns, and investigate the underlying causes of security incidents. It involves processing log entries, extracting relevant event features, identifying abnormal activity sequences, and correlating related events to understand how potential attacks develop over time. By combining probabilistic sequence modeling, machine learning-based event classification, and local large language model-assisted analysis, this approach helps detect attack patterns, identify relationships between security events, and generate meaningful explanations of potential incident causes. The resulting insights support faster threat identification, improved incident investigation, evidence-based security decisions, and timely implementation of appropriate defensive measures.