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Id15386bba-dc70-463f-a09f-d392e7731c63
RulenameInsider Risk_Risky User Access By Application
DescriptionThis alert evaluates Microsoft Entra ID Sign in risk via Machine Learning correlations in the basket operator. The basket threshold is adjustable, and the default is set to .01. There is an optional configuration to configure the percentage rates. The correlations are designed to leverage machine learning to identify patterns of risky user application access. There is an option for configuration of correlations against Microsoft Sentinel watchlists. For more information, see Tutorial: Use risk detections for user sign-ins to trigger Microsoft Entra ID Multi-Factor Authentication or password changes
SeverityMedium
TacticsExecution
TechniquesT1204
Required data connectorsAzureActiveDirectory
KindScheduled
Query frequency6h
Query period6h
Trigger threshold0
Trigger operatorgt
Source Urihttps://github.com/Azure/Azure-Sentinel/blob/master/Solutions/MicrosoftPurviewInsiderRiskManagement/Analytic%20Rules/InsiderRiskyAccessByApplication.yaml
Version1.1.4
Arm template15386bba-dc70-463f-a09f-d392e7731c63.json
Deploy To Azure
SigninLogs
| where RiskState == "atRisk"
| project UserPrincipalName, Location, AppDisplayName, RiskState
| evaluate basket(0.01) // Adjust & Tune Thresholds within Organzational Requirements
// | where Percent > 50 // Adjust & Tune Thresholds within Organzational Requirements
| where UserPrincipalName <> ""
| where AppDisplayName <> ""
| project Percent, UserPrincipalName, Location, AppDisplayName, RiskState
// | lookup kind=inner _GetWatchlist('<Your Watchlist Name>') on $left.UserPrincipalName == $right.SearchKey
| sort by Percent desc
| extend AccountName = tostring(split(UserPrincipalName, "@")[0]), AccountUPNSuffix = tostring(split(UserPrincipalName, "@")[1])
incidentConfiguration:
  createIncident: true
  groupingConfiguration:
    groupByEntities:
    - Account
    enabled: true
    matchingMethod: Selected
    reopenClosedIncident: true
    lookbackDuration: 3d
entityMappings:
- entityType: Account
  fieldMappings:
  - columnName: UserPrincipalName
    identifier: FullName
  - columnName: AccountName
    identifier: Name
  - columnName: AccountUPNSuffix
    identifier: UPNSuffix
query: |
  SigninLogs
  | where RiskState == "atRisk"
  | project UserPrincipalName, Location, AppDisplayName, RiskState
  | evaluate basket(0.01) // Adjust & Tune Thresholds within Organzational Requirements
  // | where Percent > 50 // Adjust & Tune Thresholds within Organzational Requirements
  | where UserPrincipalName <> ""
  | where AppDisplayName <> ""
  | project Percent, UserPrincipalName, Location, AppDisplayName, RiskState
  // | lookup kind=inner _GetWatchlist('<Your Watchlist Name>') on $left.UserPrincipalName == $right.SearchKey
  | sort by Percent desc
  | extend AccountName = tostring(split(UserPrincipalName, "@")[0]), AccountUPNSuffix = tostring(split(UserPrincipalName, "@")[1])
id: 15386bba-dc70-463f-a09f-d392e7731c63
queryFrequency: 6h
eventGroupingSettings:
  aggregationKind: SingleAlert
version: 1.1.4
severity: Medium
relevantTechniques:
- T1204
name: Insider Risk_Risky User Access By Application
kind: Scheduled
tactics:
- Execution
requiredDataConnectors:
- dataTypes:
  - SigninLogs
  connectorId: AzureActiveDirectory
description: |
  'This alert evaluates Microsoft Entra ID Sign in risk via Machine Learning correlations in the basket operator. The basket threshold is adjustable, and the default is set to .01. There is an optional configuration to configure the percentage rates. The correlations are designed to leverage machine learning to identify patterns of risky user application access. There is an option for configuration of correlations against Microsoft Sentinel watchlists. For more information, see [Tutorial: Use risk detections for user sign-ins to trigger Microsoft Entra ID Multi-Factor Authentication or password changes](https://docs.microsoft.com/azure/active-directory/authentication/tutorial-risk-based-sspr-mfa)'
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/MicrosoftPurviewInsiderRiskManagement/Analytic%20Rules/InsiderRiskyAccessByApplication.yaml
triggerOperator: gt
triggerThreshold: 0
queryPeriod: 6h
{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {
    "workspace": {
      "type": "String"
    }
  },
  "resources": [
    {
      "apiVersion": "2024-01-01-preview",
      "id": "[concat(resourceId('Microsoft.OperationalInsights/workspaces/providers', parameters('workspace'), 'Microsoft.SecurityInsights'),'/alertRules/15386bba-dc70-463f-a09f-d392e7731c63')]",
      "kind": "Scheduled",
      "name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/15386bba-dc70-463f-a09f-d392e7731c63')]",
      "properties": {
        "alertRuleTemplateName": "15386bba-dc70-463f-a09f-d392e7731c63",
        "customDetails": null,
        "description": "'This alert evaluates Microsoft Entra ID Sign in risk via Machine Learning correlations in the basket operator. The basket threshold is adjustable, and the default is set to .01. There is an optional configuration to configure the percentage rates. The correlations are designed to leverage machine learning to identify patterns of risky user application access. There is an option for configuration of correlations against Microsoft Sentinel watchlists. For more information, see [Tutorial: Use risk detections for user sign-ins to trigger Microsoft Entra ID Multi-Factor Authentication or password changes](https://docs.microsoft.com/azure/active-directory/authentication/tutorial-risk-based-sspr-mfa)'\n",
        "displayName": "Insider Risk_Risky User Access By Application",
        "enabled": true,
        "entityMappings": [
          {
            "entityType": "Account",
            "fieldMappings": [
              {
                "columnName": "UserPrincipalName",
                "identifier": "FullName"
              },
              {
                "columnName": "AccountName",
                "identifier": "Name"
              },
              {
                "columnName": "AccountUPNSuffix",
                "identifier": "UPNSuffix"
              }
            ]
          }
        ],
        "eventGroupingSettings": {
          "aggregationKind": "SingleAlert"
        },
        "incidentConfiguration": {
          "createIncident": true,
          "groupingConfiguration": {
            "enabled": true,
            "groupByEntities": [
              "Account"
            ],
            "lookbackDuration": "P3D",
            "matchingMethod": "Selected",
            "reopenClosedIncident": true
          }
        },
        "OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/MicrosoftPurviewInsiderRiskManagement/Analytic%20Rules/InsiderRiskyAccessByApplication.yaml",
        "query": "SigninLogs\n| where RiskState == \"atRisk\"\n| project UserPrincipalName, Location, AppDisplayName, RiskState\n| evaluate basket(0.01) // Adjust & Tune Thresholds within Organzational Requirements\n// | where Percent > 50 // Adjust & Tune Thresholds within Organzational Requirements\n| where UserPrincipalName <> \"\"\n| where AppDisplayName <> \"\"\n| project Percent, UserPrincipalName, Location, AppDisplayName, RiskState\n// | lookup kind=inner _GetWatchlist('<Your Watchlist Name>') on $left.UserPrincipalName == $right.SearchKey\n| sort by Percent desc\n| extend AccountName = tostring(split(UserPrincipalName, \"@\")[0]), AccountUPNSuffix = tostring(split(UserPrincipalName, \"@\")[1])\n",
        "queryFrequency": "PT6H",
        "queryPeriod": "PT6H",
        "severity": "Medium",
        "subTechniques": [],
        "suppressionDuration": "PT1H",
        "suppressionEnabled": false,
        "tactics": [
          "Execution"
        ],
        "techniques": [
          "T1204"
        ],
        "templateVersion": "1.1.4",
        "triggerOperator": "GreaterThan",
        "triggerThreshold": 0
      },
      "type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
    }
  ]
}