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Detect unauthorized data transfers using timeseries anomaly (ASIM Web Session)

This query utilizes built-in KQL anomaly detection algorithms to identify anomalous data transfers to public networks. It detects significant deviations from a baseline pattern, allowing the detection of sudden…

Description

This query utilizes built-in KQL anomaly detection algorithms to identify anomalous data transfers to public networks. It detects significant deviations from a baseline pattern, allowing the detection of sudden increases in data transferred to unknown public networks, which may indicate data exfiltration attempts. Investigating such anomalies is crucial. The score indicates the degree to which the data transfer deviates from the baseline value. A higher score indicates a greater deviation. The query's output provides an aggregated summary view of the traffic observed in the flagged anomaly hour, including unique combinations of source IP addresses, destination IP addresses, and port bytes sent. It may be necessary to run queries for individual source IP addresses from the provided 'SourceIPlist' to identify any suspicious activity that warrants further investigation

Detection logic

Detection requirements

Platform
ESXiLinuxmacOSWindows

The rule states no platform. This is derived from the ATT&CK technique it maps to.

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