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Open Cyber threat intelligence (OpenCTI) information is available in anunstructured format from heterogeneous sources on the Internet. We presentCyNER, an open-source python library for cybersecurity named entity recognition(NER). CyNER combines transformer-based models for extractingcybersecurity-related entities, heuristics for extracting different indicatorsof compromise, and publicly available NER models for generic entity types. Weprovide models trained on a diverse corpus that users can readily use. Eventsare described as classes in previous research - MALOnt2.0 (Christian et al.,2021) and MALOnt (Rastogi et al., 2020) and together extract a wide range ofmalware attack details from a threat intelligence corpus. The user can combinepredictions from multiple different approaches to suit their needs. The libraryis made publicly available.

CyNER: A Python Library for Cybersecurity Named Entity Recognition