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Query Details

Indicator Of Token Replay Sign In Activity Outside Of Mde Device IP Addresses

Query

let User = "AccountName";
let PublicIp = (DeviceInfo
| mv-expand todynamic(LoggedOnUsers)
| extend ParsedLoggedOnUsers = parse_json(LoggedOnUsers)
| extend LoggedOnUser = tostring(ParsedLoggedOnUsers.UserName)
| where LoggedOnUser contains User
| distinct PublicIP);
EntraIdSignInEvents
| where AccountUpn contains User and IPAddress !in (PublicIp)
| project Timestamp, Application, ResourceDisplayName, LogonType, ErrorCode, SessionId, IPAddress, Country
| join kind=inner (EntraIdSignInEvents | where IPAddress in (PublicIp)) on $left.SessionId == $right.SessionId
| distinct Timestamp, SessionId, Application, ResourceDisplayName, Country, IPAddress, ErrorCode

// Show only event with IPC alerts on SessionId
//| join kind=innerunique (AlertEvidence | extend SessionId = tostring(todynamic(AdditionalFields).SessionId)) on $left.SessionId == $right.SessionId
//| distinct Application, ResourceDisplayName, Country, IPAddress, ErrorCode, DetectionSource, Title

// Show only event with IPC alerts on IPAddress
//| join kind=innerunique (AlertEvidence | extend SessionId = tostring(todynamic(AdditionalFields).SessionId)) on $left.IPAddress == $right.RemoteIP
//| distinct Application, ResourceDisplayName, Country, IPAddress, ErrorCode, DetectionSource, Title

Explanation

This KQL query is designed to analyze and correlate sign-in events and potential security alerts related to a specific user account. Here's a simplified breakdown of what the query does:

  1. Identify Public IPs:

    • It starts by defining a user account (User = "AccountName").
    • It extracts and expands the list of users logged onto devices (DeviceInfo table) to find the specific user.
    • It collects distinct public IP addresses associated with this user's logins.

  2. Filter Sign-In Events:

    • It then looks at sign-in events (EntraIdSignInEvents) for the specified user.
    • It filters out events where the IP address is not in the list of previously identified public IPs.

  3. Project Relevant Information:

    • From these filtered events, it selects specific fields like timestamp, application, resource name, logon type, error code, session ID, IP address, and country.

  4. Correlate with Known IPs:

    • It performs an inner join on the SessionId to correlate these events with those that have known public IPs.
    • It ensures that only distinct combinations of timestamp, session ID, application, resource name, country, IP address, and error code are retained.

  5. Optional Alert Correlation:

    • The query includes commented-out sections that, if activated, would further refine the results by joining with AlertEvidence to find events with specific security alerts.
    • These sections allow for additional filtering based on alerts related to session IDs or IP addresses, showing only events with security alerts.

In essence, the query is used to identify and analyze sign-in events for a specific user, focusing on those that occur from unexpected IP addresses, and optionally correlating these with security alerts for further investigation.

Details

Thomas Naunheim profile picture

Thomas Naunheim

Released: November 8, 2025

Tables

DeviceInfoEntraIdSignInEvents

Keywords

DeviceInfoEntraIdSignInEventsAlertEvidence

Operators

letmv-expandtodynamicextendparse_jsontostringwherecontainsdistinctinprojectjoinon==!inkind=innerkind=innerunique

Actions