let starttime = 14d;
let endtime = 1d;
let timeframe = 1d;
let TotalEventsThreshold = 25;
let TimeSeriesData = AzureActivity
| where TimeGenerated between (startofday(ago(starttime))..startofday(now()))
| where OperationNameValue endswith "delete"
| project TimeGenerated, Caller
| make-series Total = count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step timeframe by Caller;
TimeSeriesData
| extend (anomalies, score, baseline) = series_decompose_anomalies(Total, 3, -1, 'linefit')
| mv-expand Total to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long)
| where TimeGenerated >= startofday(ago(endtime))
| where anomalies > 0
| project Caller, TimeGenerated, Total, baseline, anomalies, score
| where Total > TotalEventsThreshold and baseline > 0
| join (AzureActivity
| where TimeGenerated > startofday(ago(endtime))
| where OperationNameValue endswith "delete"
| summarize count(), make_set(OperationNameValue,100), make_set(_ResourceId,100) by bin(TimeGenerated, timeframe), Caller ) on TimeGenerated, Caller
| extend Name = iif(Caller has '@',tostring(split(Caller,'@',0)[0]),"")
| extend UPNSuffix = iif(Caller has '@',tostring(split(Caller,'@',1)[0]),"")
| extend AadUserId = iif(Caller !has '@',Caller,"")
tags:
- DEV-0537
entityMappings:
- entityType: Account
fieldMappings:
- identifier: FullName
columnName: Caller
- identifier: Name
columnName: Name
- identifier: UPNSuffix
columnName: UPNSuffix
- entityType: Account
fieldMappings:
- identifier: AadUserId
columnName: AadUserId
tactics:
- Impact
requiredDataConnectors:
- dataTypes:
- AzureActivity
connectorId: AzureActivity
id: ed43bdb7-eaab-4ea4-be52-6951fcfa7e3b
severity: Medium
status: Available
query: |
let starttime = 14d;
let endtime = 1d;
let timeframe = 1d;
let TotalEventsThreshold = 25;
let TimeSeriesData = AzureActivity
| where TimeGenerated between (startofday(ago(starttime))..startofday(now()))
| where OperationNameValue endswith "delete"
| project TimeGenerated, Caller
| make-series Total = count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step timeframe by Caller;
TimeSeriesData
| extend (anomalies, score, baseline) = series_decompose_anomalies(Total, 3, -1, 'linefit')
| mv-expand Total to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long)
| where TimeGenerated >= startofday(ago(endtime))
| where anomalies > 0
| project Caller, TimeGenerated, Total, baseline, anomalies, score
| where Total > TotalEventsThreshold and baseline > 0
| join (AzureActivity
| where TimeGenerated > startofday(ago(endtime))
| where OperationNameValue endswith "delete"
| summarize count(), make_set(OperationNameValue,100), make_set(_ResourceId,100) by bin(TimeGenerated, timeframe), Caller ) on TimeGenerated, Caller
| extend Name = iif(Caller has '@',tostring(split(Caller,'@',0)[0]),"")
| extend UPNSuffix = iif(Caller has '@',tostring(split(Caller,'@',1)[0]),"")
| extend AadUserId = iif(Caller !has '@',Caller,"")
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Azure Activity/Analytic Rules/TimeSeriesAnomaly_Mass_Cloud_Resource_Deletions.yaml
kind: Scheduled
queryPeriod: 14d
version: 2.0.4
name: Mass Cloud resource deletions Time Series Anomaly
queryFrequency: 1d
triggerThreshold: 0
relevantTechniques:
- T1485
description: |
'This query generates the baseline pattern of cloud resource deletions by an individual and generates an anomaly when any unusual spike is detected. These anomalies from unusual or privileged users could be an indication of a cloud infrastructure takedown by an adversary.'
triggerOperator: gt