  Malware threat intelligence uncovers deep information about malware, threat
actors, and their tactics, Indicators of Compromise(IoC), and vulnerabilities
in different platforms from scattered threat sources. This collective
information can guide decision making in cyber defense applications utilized by
security operation centers(SoCs). In this paper, we introduce an open-source
malware ontology - MALOnt that allows the structured extraction of information
and knowledge graph generation, especially for threat intelligence. The
knowledge graph that uses MALOnt is instantiated from a corpus comprising
hundreds of annotated malware threat reports. The knowledge graph enables the
analysis, detection, classification, and attribution of cyber threats caused by
malware. We also demonstrate the annotation process using MALOnt on exemplar
threat intelligence reports. A work in progress, this research is part of a
larger effort towards auto-generation of knowledge graphs (KGs)for gathering
malware threat intelligence from heterogeneous online resources.
