Alert triage can be a very cumbersome and time consuming process for SOC teams. Our recent State of Security report found that 26% of respondents agree that the volume of alerts they deal with makes it difficult to keep up with addressing emergencies. While tools like virtual sandboxes can help analysts better test and understand the severity of the threats they encounter, the process of testing and documenting results can add further tedium to an already prolonged process.

Time is of the essence when it comes to protecting your data, and often, teams are sifting through hundreds or thousands of alerts to try to pinpoint truly malicious user behavior. Manual triage and response takes up valuable resources, so machine learning can help busy teams prioritize what to tackle first and determine what warrants further investigation.