let szOperationNames = dynamic(["microsoft.compute/virtualMachines/write", "microsoft.resources/deployments/write"]);
let starttime = 7d;
let endtime = 1d;
let timeframe = 1d;
let TimeSeriesData =
AzureActivity
| where TimeGenerated between (startofday(ago(starttime)) .. startofday(now()))
| where OperationNameValue in~ (szOperationNames)
| 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 and baseline > 0
| project Caller, TimeGenerated, Total, baseline, anomalies, score
| join (AzureActivity
| where TimeGenerated > startofday(ago(endtime))
| where OperationNameValue in~ (szOperationNames)
| summarize make_set(OperationNameValue,100), make_set(_ResourceId,100), make_set(CallerIpAddress,100) by bin(TimeGenerated, timeframe), Caller
) on TimeGenerated, Caller
| mv-expand CallerIpAddress=set_CallerIpAddress
| project-away Caller1
| 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:
- identifier: FullName
columnName: Caller
- identifier: Name
columnName: Name
- identifier: UPNSuffix
columnName: UPNSuffix
- entityType: Account
fieldMappings:
- identifier: AadUserId
columnName: AadUserId
- entityType: IP
fieldMappings:
- identifier: Address
columnName: CallerIpAddress
tactics:
- Impact
requiredDataConnectors:
- dataTypes:
- AzureActivity
connectorId: AzureActivity
id: 361dd1e3-1c11-491e-82a3-bb2e44ac36ba
severity: Medium
status: Available
query: |
let szOperationNames = dynamic(["microsoft.compute/virtualMachines/write", "microsoft.resources/deployments/write"]);
let starttime = 7d;
let endtime = 1d;
let timeframe = 1d;
let TimeSeriesData =
AzureActivity
| where TimeGenerated between (startofday(ago(starttime)) .. startofday(now()))
| where OperationNameValue in~ (szOperationNames)
| 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 and baseline > 0
| project Caller, TimeGenerated, Total, baseline, anomalies, score
| join (AzureActivity
| where TimeGenerated > startofday(ago(endtime))
| where OperationNameValue in~ (szOperationNames)
| summarize make_set(OperationNameValue,100), make_set(_ResourceId,100), make_set(CallerIpAddress,100) by bin(TimeGenerated, timeframe), Caller
) on TimeGenerated, Caller
| mv-expand CallerIpAddress=set_CallerIpAddress
| project-away Caller1
| 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/Creating_Anomalous_Number_Of_Resources_detection.yaml
kind: Scheduled
queryPeriod: 7d
version: 2.0.4
name: Suspicious number of resource creation or deployment activities
queryFrequency: 1d
triggerThreshold: 0
relevantTechniques:
- T1496
description: |
'Indicates when an anomalous number of VM creations or deployment activities occur in Azure via the AzureActivity log. This query generates the baseline pattern of cloud resource creation 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