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,"")
name: Mass Cloud resource deletions Time Series Anomaly
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,"")
entityMappings:
- entityType: Account
fieldMappings:
- columnName: Caller
identifier: FullName
- columnName: Name
identifier: Name
- columnName: UPNSuffix
identifier: UPNSuffix
- entityType: Account
fieldMappings:
- columnName: AadUserId
identifier: AadUserId
queryPeriod: 14d
version: 2.0.4
tactics:
- Impact
triggerOperator: gt
kind: Scheduled
triggerThreshold: 0
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Azure Activity/Analytic Rules/TimeSeriesAnomaly_Mass_Cloud_Resource_Deletions.yaml
relevantTechniques:
- T1485
id: ed43bdb7-eaab-4ea4-be52-6951fcfa7e3b
tags:
- DEV-0537
severity: Medium
requiredDataConnectors:
- connectorId: AzureActivity
dataTypes:
- AzureActivity
status: Available
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.'
queryFrequency: 1d