  Tags can be used by malware repositories and analysis services to enable
searches for samples of interest across different dimensions. Automatically
extracting tags from AV labels is an efficient approach to categorize and index
massive amounts of samples. Recent tools like AVClass and Euphony have
demonstrated that, despite their noisy nature, it is possible to extract family
names from AV labels. However, beyond the family name, AV labels contain much
valuable information such as malware classes, file properties, and behaviors.
  This work presents AVClass2, an automatic malware tagging tool that given the
AV labels for a potentially massive number of samples, extracts clean tags that
categorize the samples. AVClass2 uses, and helps building, an open taxonomy
that organizes concepts in AV labels, but is not constrained to a predefined
set of tags. To keep itself updated as AV vendors introduce new tags, it
provides an update module that automatically identifies new taxonomy entries,
as well as tagging and expansion rules that capture relations between tags. We
have evaluated AVClass2 on 42M and showed how it enables advanced malware
searches and to maintain an updated knowledge base of malware concepts in AV
labels.
