Time series anomaly detection for total volume of traffic
Identifies anamalous spikes in network traffic logs as compared to baseline or normal historical patterns. The query leverages a KQL built-in anomaly detection algorithm to find large deviations from baseline…
Description
Identifies anamalous spikes in network traffic logs as compared to baseline or normal historical patterns. The query leverages a KQL built-in anomaly detection algorithm to find large deviations from baseline patterns. Sudden increases in network traffic volume may be an indication of data exfiltration attempts and should be investigated. The higher the score, the further it is from the baseline value. The output is aggregated to provide summary view of unique source IP to destination IP address and port traffic observed in the flagged anomaly hour. The source IP addresses which were sending less than percentotalthreshold of the total traffic have been exluded whose value can be adjusted as needed . You may have to run queries for individual source IP addresses from SourceIPlist to determine if anything looks suspicious
Detection logic
Detection requirements
- Platform
- ESXiLinuxmacOSWindows
The rule states no platform. This is derived from the ATT&CK technique it maps to.
- Log source product
- barracudacefcheckpointciscoasaf5fortinetpaloaltonetworks
- Log source service
- commonsecuritylog
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
- 06a9b845-6a95-4432-a78b-83919b28c375
- Tagged by the source as
- ExfiltrationSecurity - Others
Licence
- Published under
- MIT LicenseRead the licence
- Attribution
- Required
- Obtained under
- MITRead the origin licence
Authorship
- Written by
- Published
- Sep 2, 2026
- Version
- 1