Anomaly Sign In Event from an IP

let LookBack = 1h;
let Data = (
SigninLogs
| where TimeGenerated >= ago(LookBack)
| where parse_json(NetworkLocationDetails)[0].networkType != "trustedNamedLocation" // Excludes known tagged networks
// Counts the number of sign in events in the last hour every 15 minutes by IP
| make-series EventCounts = count() on TimeGenerated from ago(LookBack) to now() step 15m by IPAddress 
);
let AnomalyAlert = (
Data
| extend (Anomalies, Score, Baseline) = series_decompose_anomalies(EventCounts,1.5,-1,'linefit')
| mv-expand EventCounts,TimeGenerated,Anomalies to typeof(double),Baseline to typeof(long),Score to typeof(double)
| where Anomalies > 0
);
AnomalyAlert
| join kind = inner (SigninLogs
| where TimeGenerated between (ago(LookBack) .. now())
| where parse_json(NetworkLocationDetails)[0].networkType != "trustedNamedLocation"
| extend PasswordResult = tostring(parse_json(AuthenticationDetails).authenticationStepResultDetail)
| summarize UserCount = dcount(UserPrincipalName), UserList = make_set(UserPrincipalName), AppName = make_set(AppDisplayName), PasswordResult = make_list(PasswordResult) by IPAddress) on IPAddress
| where PasswordResult has "Correct Password"
| where UserCount > 1 // looks for events targeting more than one user.

relevantTechniques:
- T1078
entityMappings:
- fieldMappings:
  - columnName: IPAddress
    identifier: Address
  entityType: IP
triggerThreshold: 0
description: |
    'Identifies sign-in anomalies from an IP in the last hour, targeting multiple users where the password is correct after multiple attempts'
metadata:
  author:
    name: Juanse
  source:
    kind: Community
  categories:
    domains:
    - Identity
  support:
    tier: Community
customDetails:
  AppName: AppName
  Baseline: Baseline
  Score: Score
  UserList: UserList
  UserCount: UserCount
  PasswordResult: PasswordResult
requiredDataConnectors:
- connectorId: AzureActiveDirectory
  dataTypes:
  - SigninLogs
triggerOperator: gt
version: 1.0.1
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Detections/Anomalies/SignInAnomaly.yaml
id: 9c1e9381-79dd-4ddf-9570-b73a1dc59fe0
queryFrequency: 1h
query: |
  let LookBack = 1h;
  let Data = (
  SigninLogs
  | where TimeGenerated >= ago(LookBack)
  | where parse_json(NetworkLocationDetails)[0].networkType != "trustedNamedLocation" // Excludes known tagged networks
  // Counts the number of sign in events in the last hour every 15 minutes by IP
  | make-series EventCounts = count() on TimeGenerated from ago(LookBack) to now() step 15m by IPAddress 
  );
  let AnomalyAlert = (
  Data
  | extend (Anomalies, Score, Baseline) = series_decompose_anomalies(EventCounts,1.5,-1,'linefit')
  | mv-expand EventCounts,TimeGenerated,Anomalies to typeof(double),Baseline to typeof(long),Score to typeof(double)
  | where Anomalies > 0
  );
  AnomalyAlert
  | join kind = inner (SigninLogs
  | where TimeGenerated between (ago(LookBack) .. now())
  | where parse_json(NetworkLocationDetails)[0].networkType != "trustedNamedLocation"
  | extend PasswordResult = tostring(parse_json(AuthenticationDetails).authenticationStepResultDetail)
  | summarize UserCount = dcount(UserPrincipalName), UserList = make_set(UserPrincipalName), AppName = make_set(AppDisplayName), PasswordResult = make_list(PasswordResult) by IPAddress) on IPAddress
  | where PasswordResult has "Correct Password"
  | where UserCount > 1 // looks for events targeting more than one user.  
severity: Medium
queryPeriod: 1h
name: Anomaly Sign In Event from an IP
tactics:
- InitialAccess
kind: Scheduled