Abstract: A method comprises obtaining at least a first software module not classified as benign or potentially malicious, extracting a set of features associated with the first software module, the set of features comprising static features, behavior features and context features, identifying a first cluster comprising one or more known software modules previously classified as benign, computing distance metrics between the extracted feature set of the first software module and feature sets of respective ones of the known software modules in the first cluster, classifying the first software module as one of benign and potentially malicious based on a comparison between the computed distance metrics and a neighborhood distance metric based on distances between feature sets of the known software modules in the first cluster, and modifying access by a given client device to the first software module responsive to classifying the first software module as potentially malicious.

Abstract: A method comprises obtaining at least a first software module not classified as benign or potentially malicious, extracting a set of features associated with the first software module including static, behavior and context features, computing distance metrics between the extracted feature set and feature sets of a plurality of clusters including one or more clusters of software modules previously classified as benign and exhibiting a first threshold level of similarity relative to one another and one or more clusters of software modules previously classified as potentially malicious and exhibiting a second threshold level of similarity relative to one another, classifying the first software module as belonging to a given cluster based at least in part on the computed distance metrics, and modifying access by a given client device to the first software module responsive to the given cluster being a cluster of software modules previously classified as potentially malicious.