GapFinder is a system for identifying semantic inconsistencies within cybersecurity domain texts. It examines technical inconsistencies that arise in functional descriptions of open source malware threat reporting information from various web-based sources. GapFinder utilizes natural language processing to transform unstructured text into structured forms that can then be analyzed to detect the presence of inconsistencies across different reports on the same malware threats. The system was evaluated using tens of thousands of relations derived from web-based malware threat reports, demonstrating its ability to successfully identify inconsistencies between different descriptions of the same threats.