Privileged Accounts - Sign in Failure Spikes

let starttime = 14d;
let timeframe = 1d;
let scorethreshold = 3;
let baselinethreshold = 5;
let aadFunc = (tableName:string){
    IdentityInfo
    | where TimeGenerated > ago(starttime)
    | summarize arg_max(TimeGenerated, *) by AccountUPN
    | mv-expand AssignedRoles
    | where AssignedRoles contains 'Admin' or GroupMembership has "Admin"
    | summarize Roles = make_list(AssignedRoles) by AccountUPN = tolower(AccountUPN)
    | join kind=inner (
        table(tableName)
        | where TimeGenerated between (startofday(ago(starttime))..startofday(now()))
        | where ResultType != 0
        | extend UserPrincipalName = tolower(UserPrincipalName)
    ) on $left.AccountUPN == $right.UserPrincipalName
    | extend timestamp = TimeGenerated, AccountCustomEntity = UserPrincipalName, Roles = tostring(Roles)
};
let aadSignin = aadFunc("SigninLogs");
let aadNonInt = aadFunc("AADNonInteractiveUserSignInLogs");
let allSignins = union isfuzzy=true aadSignin, aadNonInt;
let TimeSeriesAlerts = 
    allSignins
    | make-series HourlyCount=count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step 1h by UserPrincipalName, Roles
    | extend (anomalies, score, baseline) = series_decompose_anomalies(HourlyCount, scorethreshold, -1, 'linefit')
    | mv-expand HourlyCount to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long)
    // Filtering low count events per baselinethreshold
    | where anomalies > 0 and baseline > baselinethreshold
    | extend AnomalyHour = TimeGenerated
    | project UserPrincipalName, Roles, AnomalyHour, TimeGenerated, HourlyCount, baseline, anomalies, score;
// Filter the alerts for specified timeframe
TimeSeriesAlerts
| where TimeGenerated > startofday(ago(timeframe))
| join kind=inner ( 
    allSignins
    | where TimeGenerated > startofday(ago(timeframe))
    // create a new column and round to hour
    | extend DateHour = bin(TimeGenerated, 1h)
    | summarize PartialFailedSignins = count(), LatestAnomalyTime = arg_max(TimeGenerated, *) by bin(TimeGenerated, 1h), OperationName, Category, ResultType, ResultDescription, UserPrincipalName, Roles, UserDisplayName, AppDisplayName, ClientAppUsed, IPAddress, ResourceDisplayName
) on UserPrincipalName, $left.AnomalyHour == $right.DateHour
| project LatestAnomalyTime, OperationName, Category, UserPrincipalName, Roles = todynamic(Roles), UserDisplayName, ResultType, ResultDescription, AppDisplayName, ClientAppUsed, UserAgent, IPAddress, Location, AuthenticationRequirement, ConditionalAccessStatus, ResourceDisplayName, PartialFailedSignins, TotalFailedSignins = HourlyCount, baseline, anomalies, score
| extend Name = tostring(split(UserPrincipalName,'@',0)[0]), UPNSuffix = tostring(split(UserPrincipalName,'@',1)[0])

relevantTechniques:
- T1078.004
entityMappings:
- fieldMappings:
  - columnName: UserPrincipalName
    identifier: FullName
  - columnName: Name
    identifier: Name
  - columnName: UPNSuffix
    identifier: UPNSuffix
  entityType: Account
- fieldMappings:
  - columnName: IPAddress
    identifier: Address
  entityType: IP
triggerThreshold: 0
description: |
  ' Identifies spike in failed sign-ins from Privileged accounts. Privileged accounts list can be based on IdentityInfo UEBA table.
  Spike is determined based on Time series anomaly which will look at historical baseline values.
  Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-privileged-accounts#things-to-monitor'  
requiredDataConnectors:
- connectorId: AzureActiveDirectory
  dataTypes:
  - SigninLogs
- connectorId: AzureActiveDirectory
  dataTypes:
  - AADNonInteractiveUserSignInLogs
- connectorId: BehaviorAnalytics
  dataTypes:
  - IdentityInfo
triggerOperator: gt
version: 1.1.1
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Microsoft Entra ID/Analytic Rules/PrivilegedAccountsSigninFailureSpikes.yaml
id: 34c5aff9-a8c2-4601-9654-c7e46342d03b
queryFrequency: 1d
query: |
  let starttime = 14d;
  let timeframe = 1d;
  let scorethreshold = 3;
  let baselinethreshold = 5;
  let aadFunc = (tableName:string){
      IdentityInfo
      | where TimeGenerated > ago(starttime)
      | summarize arg_max(TimeGenerated, *) by AccountUPN
      | mv-expand AssignedRoles
      | where AssignedRoles contains 'Admin' or GroupMembership has "Admin"
      | summarize Roles = make_list(AssignedRoles) by AccountUPN = tolower(AccountUPN)
      | join kind=inner (
          table(tableName)
          | where TimeGenerated between (startofday(ago(starttime))..startofday(now()))
          | where ResultType != 0
          | extend UserPrincipalName = tolower(UserPrincipalName)
      ) on $left.AccountUPN == $right.UserPrincipalName
      | extend timestamp = TimeGenerated, AccountCustomEntity = UserPrincipalName, Roles = tostring(Roles)
  };
  let aadSignin = aadFunc("SigninLogs");
  let aadNonInt = aadFunc("AADNonInteractiveUserSignInLogs");
  let allSignins = union isfuzzy=true aadSignin, aadNonInt;
  let TimeSeriesAlerts = 
      allSignins
      | make-series HourlyCount=count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step 1h by UserPrincipalName, Roles
      | extend (anomalies, score, baseline) = series_decompose_anomalies(HourlyCount, scorethreshold, -1, 'linefit')
      | mv-expand HourlyCount to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long)
      // Filtering low count events per baselinethreshold
      | where anomalies > 0 and baseline > baselinethreshold
      | extend AnomalyHour = TimeGenerated
      | project UserPrincipalName, Roles, AnomalyHour, TimeGenerated, HourlyCount, baseline, anomalies, score;
  // Filter the alerts for specified timeframe
  TimeSeriesAlerts
  | where TimeGenerated > startofday(ago(timeframe))
  | join kind=inner ( 
      allSignins
      | where TimeGenerated > startofday(ago(timeframe))
      // create a new column and round to hour
      | extend DateHour = bin(TimeGenerated, 1h)
      | summarize PartialFailedSignins = count(), LatestAnomalyTime = arg_max(TimeGenerated, *) by bin(TimeGenerated, 1h), OperationName, Category, ResultType, ResultDescription, UserPrincipalName, Roles, UserDisplayName, AppDisplayName, ClientAppUsed, IPAddress, ResourceDisplayName
  ) on UserPrincipalName, $left.AnomalyHour == $right.DateHour
  | project LatestAnomalyTime, OperationName, Category, UserPrincipalName, Roles = todynamic(Roles), UserDisplayName, ResultType, ResultDescription, AppDisplayName, ClientAppUsed, UserAgent, IPAddress, Location, AuthenticationRequirement, ConditionalAccessStatus, ResourceDisplayName, PartialFailedSignins, TotalFailedSignins = HourlyCount, baseline, anomalies, score
  | extend Name = tostring(split(UserPrincipalName,'@',0)[0]), UPNSuffix = tostring(split(UserPrincipalName,'@',1)[0])  
severity: High
kind: Scheduled
status: Available
queryPeriod: 14d
name: Privileged Accounts - Sign in Failure Spikes
tactics:
- InitialAccess
tags:
- AADSecOpsGuide