Advanced Persistent Threat (APT) generates Cyber Threat Intelligence (CTI) reports in the form of unstructured text that is difficult to analyze efficiently. This study aims to extract structured information from CTI reports using the Named Entity Recognition (NER) approach with the Bidirectional Long Short-Term Memory–Conditional Random Field (BiLSTM-CRF) model. The dataset used is CyberNER …