↳ Source GitHubRègle analytiqueMedium

Anomalous login followed by Teams action

Description

'Detects anomalous IP address usage by user accounts and then checks to see if a suspicious Teams action is performed. Query calculates IP usage Delta for each user account and selects accounts where a delta >= 90% is observed between the most and least used IP. To further reduce results the query performs a prevalence check on the lowest used IP's country, only keeping IP's where the country is unusual for the tenant (dynamic ranges). Please note, if the initial logic of prevalence to find suspicious logon activity is noisy then consider adding filtering based on Location. Finally the user accounts activity within Teams logs is checked for suspicious commands (modifying user privileges or admin actions) during the period the suspicious IP was active.'
Type de règle
Scheduled
Version
1.1.2
Fréquence
1d
Période analysée
14d
Déclenchement
gt 0

Couverture MITRE déclarée

Sources déclarées

Métadonnées du fichier source. Aucune dépendance déduite du KQL.

Connecteurs

Types de données

Requête KQL

Requête originale, sans modification.

//The bigger the window the better the data sample size, as we use IP prevalence, more sample data is better.
//The minimum number of countries that the account has been accessed from [default: 2]
let minimumCountries = 2;
//The delta (%) between the largest in-use IP and the smallest [default: 95]
let deltaThreshold = 95;
//The maximum (%) threshold that the country appears in login data [default: 10]
let countryPrevalenceThreshold = 10;
//The time to project forward after the last login activity [default: 60min]
let projectedEndTime = 60m;
let queryfrequency = 1d;
let queryperiod = 14d;
let aadFunc = (tableName: string) {
    // Get successful signins to Teams
    let signinData =
        table(tableName)
        | where TimeGenerated > ago(queryperiod)
        | where AppDisplayName has "Teams" and ConditionalAccessStatus =~ "success"
        | extend Country = tostring(todynamic(LocationDetails)['countryOrRegion'])
        | where isnotempty(Country) and isnotempty(IPAddress);
    // Calculate prevalence of countries
    let countryPrevalence =
        signinData
        | summarize CountCountrySignin = count() by Country
        | extend TotalSignin = toscalar(signinData | summarize count())
        | extend CountryPrevalence = toreal(CountCountrySignin) / toreal(TotalSignin) * 100;
    // Count signins by user and IP address
    let userIpSignin =
        signinData
        | summarize CountIPSignin = count(), Country = any(Country), ListSigninTimeGenerated = make_list(TimeGenerated) by IPAddress, UserPrincipalName;
    // Calculate delta between the IP addresses with the most and minimum activity by user
    let userIpDelta =
        userIpSignin
        | summarize MaxIPSignin = max(CountIPSignin), MinIPSignin = min(CountIPSignin), DistinctCountries = dcount(Country), make_set(Country) by UserPrincipalName
        | extend UserIPDelta = toreal(MaxIPSignin - MinIPSignin) / toreal(MaxIPSignin) * 100;
    // Collect Team operations the user account has performed within a time range of the suspicious signins
    OfficeActivity
    | where TimeGenerated > ago(queryfrequency)
    | where Operation in~ ("TeamsAdminAction", "MemberAdded", "MemberRemoved", "MemberRoleChanged", "AppInstalled", "BotAddedToTeam")
    | where not (Operation in~ ("MemberAdded", "MemberRemoved") and CommunicationType in~ ("GroupChat", "OneonOne")) // These events have been noisy and are related to initiaing chat conversation and not admin operations.
    | project OperationTimeGenerated = TimeGenerated, UserId = tolower(UserId), Operation
    | join kind = inner(
        userIpDelta
        // Check users with activity from distinct countries
        | where DistinctCountries >= minimumCountries
        // Check users with high IP delta
        | where UserIPDelta >= deltaThreshold
        // Add information about signins and countries
        | join kind = leftouter userIpSignin on UserPrincipalName
        | join kind = leftouter countryPrevalence on Country
        // Check activity that comes from nonprevalent countries
        | where CountryPrevalence < countryPrevalenceThreshold
        | project
            UserPrincipalName,
            SuspiciousIP = IPAddress,
            UserIPDelta,
            SuspiciousSigninCountry = Country,
            SuspiciousCountryPrevalence = CountryPrevalence,
            EventTimes = ListSigninTimeGenerated
    ) on $left.UserId == $right.UserPrincipalName
    // Check the signins occured 60 min before the Teams operations
    | mv-expand SigninTimeGenerated = EventTimes
    | extend SigninTimeGenerated = todatetime(SigninTimeGenerated)
    | where OperationTimeGenerated between (SigninTimeGenerated .. (SigninTimeGenerated + projectedEndTime))
};
let aadSignin = aadFunc("SigninLogs");
let aadNonInt = aadFunc("AADNonInteractiveUserSignInLogs");
union isfuzzy=true aadSignin, aadNonInt
| summarize arg_max(SigninTimeGenerated, *) by UserPrincipalName, SuspiciousIP, OperationTimeGenerated
| summarize
    ActivitySummary = make_bag(pack(tostring(SigninTimeGenerated), pack("Operation", tostring(Operation), "OperationTime", OperationTimeGenerated)))
    by UserPrincipalName, SuspiciousIP, SuspiciousSigninCountry, SuspiciousCountryPrevalence
| extend AccountName = tostring(split(UserPrincipalName, "@")[0]), AccountUPNSuffix = tostring(split(UserPrincipalName, "@")[1])

Entités déclarées

AccountIP

Contenus associés

Liens établis à partir des identifiants déclarés et des manifests des solutions.

Traçabilité de la source

GitHub

Les valeurs affichées proviennent des fichiers du dépôt Azure/Azure-Sentinel. Elles décrivent le modèle publié, pas la configuration de votre workspace.

Identifiant source
2b701288-b428-4fb8-805e-e4372c574786
Autres fichiers source 1Detections/MultipleDataSources/AnomalousIPUsageFollowedByTeamsAction.yamlsource ↗
GSTEP / SUIVI DU CATALOGUE

Ajouté au catalogue : 16 sept. 2026 · 05:49 UTC
Dernier changement observé : 16 sept. 2026 · 05:49 UTC

Dates de synchronisation GSTEP, distinctes des dates de publication du contenu source.