A server-side system that detects and classifies malware and other types of undesirable processes and events operating on network connected devices through the analysis of information collected from said network connected devices. The system receives information over a network connection and collects information that is identified as being anomalous. The collected information is analyzed by system process that can group data based on optimally suited cluster analysis methods. Upon clustering the information, the system can correlate an anomalous event to device status, interaction, and various elements that constitute environmental data in order to identify a pattern of behavior associated with a known or unknown strain of malware. The system further interprets the clustered information to extrapolate propagation characteristics of the strain of malware and determine a potential response action.