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
MITRE ATT&CK mappings
0 exclusive techniques.This is coverage no other published rule has; it is not this rule's total technique count.
No references are available for this detection.
From the source
- At source
- Open at source
- Upstream identifier
- 5965d3e7-8ed0-477c-9b42-e75d9237fab0
- Tagged by the source as
- Exfiltration
Licence
- Published under
- MIT LicenseRead the licence
- Attribution
- Required
- Obtained under
- MITRead the origin licence
Authorship
- Published
- Sep 15, 2026
- Version
- 2