Suspicious number of resource creation or deployment activities

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Id	361dd1e3-1c11-491e-82a3-bb2e44ac36ba
Rulename	Suspicious number of resource creation or deployment activities
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.
Severity	Medium
Tactics	Impact
Techniques	T1496
Required data connectors	AzureActivity
Kind	Scheduled
Query frequency	1d
Query period	7d
Trigger threshold	0
Trigger operator	gt
Source Uri	https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Azure Activity/Analytic Rules/Creating_Anomalous_Number_Of_Resources_detection.yaml
Version	2.0.4
Arm template	361dd1e3-1c11-491e-82a3-bb2e44ac36ba.json

KQL

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,"")

YAML

OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Azure Activity/Analytic Rules/Creating_Anomalous_Number_Of_Resources_detection.yaml
queryPeriod: 7d
kind: Scheduled
name: Suspicious number of resource creation or deployment activities
status: Available
entityMappings:
- fieldMappings:
  - columnName: Caller
    identifier: FullName
  - columnName: Name
    identifier: Name
  - columnName: UPNSuffix
    identifier: UPNSuffix
  entityType: Account
- fieldMappings:
  - columnName: AadUserId
    identifier: AadUserId
  entityType: Account
- fieldMappings:
  - columnName: CallerIpAddress
    identifier: Address
  entityType: IP
tactics:
- Impact
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.'
severity: Medium
requiredDataConnectors:
- connectorId: AzureActivity
  dataTypes:
  - AzureActivity
queryFrequency: 1d
triggerThreshold: 0
version: 2.0.4
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,"")  
relevantTechniques:
- T1496
id: 361dd1e3-1c11-491e-82a3-bb2e44ac36ba
triggerOperator: gt

ARM