Query Details

Multiple Email Entity Signin Logs

Query

// This query assumes a feed of threat indicators is ingested/synchronized periodically, and each synchronization ingests new indicators and only old indicators that have been modified.
// Active threat indicators in Sentinel are renovated as ThreatIntelligenceIndicator events every ~12 days.
let query_frequency = 1h;
let query_period = 14d;
let query_wait = 0h;
let table_query_lookback = 14d;
let _TIBenignProperty =
    _GetWatchlist('ID-TIBenignProperty')
    | where Notes has_any ("[SourceEmailAddress]")
    | project IndicatorId, BenignProperty
;
let _TIExcludedSources = toscalar(
    _GetWatchlist('Activity-ExpectedSignificantActivity')
    | where Activity == "ThreatIndicatorSource"
    | summarize make_list(Auxiliar)
    );
let _UncompromisedFailureResultTypes = toscalar(
    _GetWatchlist('ResultType-SignInLogsErrorCodes')
    | where isnotempty(ResultDescription) and not(Notes has_any ("[Success]", "[Expired]"))
    | summarize make_list(ResultType)
    );
let _TITableMatch = (table_start: datetime, table_end: datetime, only_new_ti: boolean, ti_start: datetime = datetime(null)) {
    // Scheduled Analytics rules have a query period limit of 14d
    let _Indicators =// materialize(
        ThreatIntelligenceIndicator
        | where TimeGenerated > ago(query_period)
        // Take the earliest TimeGenerated and the latest column info
        | summarize hint.strategy=shuffle
            minTimeGenerated = min(TimeGenerated),
            arg_max(TimeGenerated, Active, Description, ActivityGroupNames, IndicatorId, ThreatType, DomainName, Url, ExpirationDateTime, ConfidenceScore, AdditionalInformation, ExternalIndicatorId, EmailSenderAddress)
            by IndicatorId
        // Remove inactive or expired indicators
        | where not(not(Active) or ExpirationDateTime < now())
        // Pick indicators that contain the desired entity type
        | where isnotempty(EmailSenderAddress)
        | extend EmailAddress = tolower(EmailSenderAddress)
        // Remove indicators from specific sources
        | where not(AdditionalInformation has_any (_TIExcludedSources) or Description has_any (_TIExcludedSources))
        // Remove excluded indicators with benign properties
        | join kind=leftanti _TIBenignProperty on IndicatorId, $left.EmailAddress == $right.BenignProperty
        // Deduplicate indicators by EmailAddress column, equivalent to using join kind=innerunique afterwards
        | summarize hint.strategy=shuffle
            minTimeGenerated = min(minTimeGenerated),
            take_any(*)
            by EmailAddress
        // If we want only new indicators, remove indicators received previously
        | where not(only_new_ti and minTimeGenerated < ti_start)
    //)
    ;
    //let _IndicatorsLength = toscalar(_Indicators | summarize count());
    //let _IndicatorsPrefilter = toscalar(
    //    _Indicators
    //    | extend AuxiliarField = tostring(split(EmailAddress, ".")[-1])
    //    | summarize make_set_if(AuxiliarField, isnotempty(AuxiliarField))
    //);
    //let _IndicatorsPrefilterLength = array_length(_IndicatorsPrefilter);
    let _TableEvents =
        SigninLogs
        | where TimeGenerated between (table_start .. table_end)
        // Filter events that may contain indicators
        //| where not(_IndicatorsPrefilterLength < 10000 and not(UserPrincipalName has_any (_IndicatorsPrefilter))) // valid TLD ~1500 , "has_any" limit 10000
        | extend EmailAddress = tolower(UserPrincipalName)
        //| where not(_IndicatorsLength < 1000000 and not(EmailAddress in (toscalar(_Indicators | summarize make_list(EmailAddress))))) // "in" limit 1.000.000
        | project-rename SigninLogs_TimeGenerated = TimeGenerated
    ;
    _Indicators
    | join kind=inner hint.strategy=shuffle _TableEvents on EmailAddress
    // Take only a single event by key columns
    //| summarize hint.strategy=shuffle take_any(*) by EmailAddress, UserId
    | extend
        DeviceDetail = tostring(DeviceDetail),
        ConditionalAccessPolicies = tostring(ConditionalAccessPolicies)
    | project
        SigninLogs_TimeGenerated,
        Description, ActivityGroupNames, IndicatorId, ThreatType, DomainName, Url, ExpirationDateTime, ConfidenceScore, AdditionalInformation, EmailSenderAddress,
        Category, UserPrincipalName, UserDisplayName, IPAddress, Location, ResultType, ResultDescription, ClientAppUsed, AppDisplayName, ResourceDisplayName, DeviceDetail, UserAgent, AuthenticationDetails, ConditionalAccessPolicies, RiskState, RiskEventTypes, RiskLevelDuringSignIn, RiskLevelAggregated, UserId, OriginalRequestId, CorrelationId
};
union// isfuzzy=true
    // Match      current table events                                all indicators available
    _TITableMatch(ago(query_frequency + query_wait), ago(query_wait), false),
    // Match      past table events                                                          new indicators since last query execution
    _TITableMatch(ago(table_query_lookback + query_wait), ago(query_frequency + query_wait), true, ago(query_frequency))
| summarize arg_max(SigninLogs_TimeGenerated, *) by IndicatorId, UserId
| extend
    DeviceDetail = tostring(DeviceDetail),
    ConditionalAccessPolicies = tostring(ConditionalAccessPolicies)
| extend
    timestamp = SigninLogs_TimeGenerated,
    IPCustomEntity = IPAddress,
    AccountCustomEntity = EmailSenderAddress

Explanation

This KQL query is designed to identify and analyze suspicious sign-in activities based on threat intelligence indicators. Here's a simplified breakdown of what the query does:

  1. Setup and Configuration:

    • Defines various time periods and parameters for the query, such as how often it should run (query_frequency), the period it should cover (query_period), and a wait time (query_wait).
  2. Threat Intelligence Indicators:

    • Retrieves a list of threat indicators from a data source, focusing on email addresses associated with threats.
    • Filters out inactive or expired indicators and those from specific excluded sources.
    • Removes indicators with benign properties, ensuring only relevant threat indicators are considered.
  3. Sign-in Logs Analysis:

    • Retrieves sign-in logs within a specified time range.
    • Matches these logs against the threat indicators based on email addresses.
    • Filters and processes the logs to identify potential security incidents.
  4. Data Processing and Output:

    • Joins the threat indicators with sign-in logs to find matches.
    • Ensures that only unique and relevant events are considered.
    • Projects and extends various fields to provide detailed information about each incident, such as user details, device information, and risk levels.
  5. Final Output:

    • Combines current and past events with new threat indicators to provide a comprehensive view of potential threats.
    • Summarizes the results to highlight the most recent and relevant incidents, including details like IP addresses and user accounts involved.

Overall, this query is used to detect and analyze sign-in activities that may be linked to known threat indicators, helping security teams to identify and respond to potential security threats effectively.

Details

Jose Sebastián Canós profile picture

Jose Sebastián Canós

Released: December 13, 2023

Tables

ThreatIntelligenceIndicatorSigninLogs

Keywords

ThreatIntelligenceIndicatorSigninLogsEmailAddressUserPrincipalNameUserIdDeviceDetailConditionalAccessPoliciesIPAddressLocationUserAgentAuthenticationDetailsRiskStateRiskEventTypesRiskLevelDuringSignInRiskLevelAggregatedOriginalRequestIdCorrelationId

Operators

let|has_anyprojecttoscalarwhereisnotemptyandnotsummarizemake_listarg_max<nowextendtolowerjoinkind=leftanti==take_anybybetween..project-renamekind=inneruniontostring

Actions

GitHub