Alert Types That Use the Linux Index

The Alert Types listed below use the Linux Index . For a list of Alert Types by each index or XDR Kill Chain stage, or for a general overview, refer to Machine Learning and Analytics Overview.

To minimize excessive alerting, each alert type is triggered only once in a 24-hour period for the set of attributes that triggered that specific alert.

Where applicable, the Tactics and Techniques are linked to the relevant MITRE | ATT&CK page.

Stellar Cyber also provides an interactive tool that lets you look up alert types by data source, alert name, event type, or source index.

File Action Anomaly

Actions, such as move, copy, delete, or change attribute, were taken on a file or files an anomalous number of times. Investigate the actions and the user to see if this is expected.

XDR Kill Chain

  • Kill Chain Stage: Exfiltration & Impact

  • Tactic: Impact (TA0040 )

  • Technique: Data Manipulation (T1565 )

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is anomalous_file_action.

Key Fields and Relevant Data Points

  • secondary — user name  
  • actual — actual number of file actions in the period
  • typical — typical number of file actions in the period
  • path — path to the file

Use Case with Data Points

The number of file actions for each user (command) is calculated periodically. If the volume (actual) is anomalous compared to the typical volume (typical) of file actions in any period, an alert is triggered. The Interflow includes the directory to the file (path).

Process Anomaly

A process has been launched an anomalously large number of times. Investigate the process and the user to see if this is expected.

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: XDR EBA (XTA0001)

  • Technique: XDR Process Anomaly (XT1001)

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is bad_process.

Key Fields and Relevant Data Points

  • process_name — name of the process 
  • hostip — host IP address
  • hostip_host — host name
  • actual — actual number of launches in the period
  • typical — typical number of launches in the period
  • process_user — user who launched the process

Use Case with Data Points

The number of times a process (process_name) has been launched is calculated periodically. If the volume (actual) is much larger than the typical volume (typical) of the command or other commands in any period, an alert is triggered. The Interflow includes the name of the user who launched the process (process_user).

Bad Reputation Login

A successful login was detected from an IP address with a history of malicious activity. Check with the user.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR NBA (XTA0002)

  • Technique: XDR Bad Reputation (XT2010)

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is bad_reputation_login.

Key Fields and Relevant Data Points

  • srcip — source IP address  
  • srcip_host — source host name
  • srcip_reputation — source reputation
  • source_geo.countryName — source country
  • dstip_host — destination host name
  • login_type — type of login
  • username — user name

Use Case with Data Points

The login records are checked for every source IP address (srcip). If a source IP address has successful login records and its reputation (srcip_reputation) is bad (except brute-forcer and scanner), an alert is triggered. A sample Interflow includes source IP address (srcip), source host (srcip_host), source reputation (srcip_reputation), source country (srcip_geo.countryName), login type (login_type), and user name (username).

Command Anomaly

A command has been executed an anomalously large number of times compared to its typical executions or those of other commands. Investigate the command and the user to determine if this is expected.

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: Execution (TA0002 )

  • Technique: Command and Scripting Interpreter (T1059 )

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is command_anomaly.

Key Fields and Relevant Data Points

  • command — command executed  
  • actual — actual number of executions in the period
  • typical — typical number of executions in the period
  • cwd — current working directory from which the command executed
  • hostip — host running the agent sensor
  • srcip — source IP address from which the command was run
  • username — user name who ran the command

Use Case with Data Points

The number of times a command (command) has been executed is calculated periodically. If the volume (actual) is much larger than the typical volume (typical) of the command or other commands in any period, an alert is triggered. The Interflow includes the directory from which the command was executed (cwd), the host and source IP addresses (hostip and srcip) from which the command was executed, and the name of the user who ran the command (username).

External Account Login Failure Anomaly

An anomalously large number of user login failures was observed for an account. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is external_cloud_account_login_failure.

Key Fields and Relevant Data Points

  • srcip_usersid — cloud account user ID  
  • scrip_username — cloud account user name
  • event_summary.total_failed — number of failed logins in the period
  • event_summary.total_successful — number of successful logins in the period
  • event_summary.total_fail_ratio — percent of failed logins in the period, which is: event_summary.total_failed / (event_summary.total_failed + event_summary.total_successful)
  • accumulated_anomalous_failures — score value of the model indicating the degree of abnormal activity
  • srcip_host — host name of corresponding source IP address
  • login_type — type of login
  • srcip_reputation — source reputation

Use Case with Data Points

Login failures and successes are calculated periodically for every account (srcip_usersid). If the number of failures is significantly larger than the number of successes, an alert is triggered. A sample Interflow includes the login type (login_type), source host (srcip_host), and source reputation (srcip_reputation).

External User Login Failure Anomaly

An anomalous number of login failures was observed for one of the following applications: SSH, SMTP, FTP, RDP, SMB, databases, Active Directory, Office 365, Okta, AWS CloudTrail, or Google Workspace. For Okta, an anomalous number of multi-factor authentication (MFA) failures was observed. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is external_user_login_fail.

Key Fields and Relevant Data Points

  • srcip — source IP address  
  • dstip — destination IP address  
  • dstip_host — destination host name
  • event_summary.total_failed — number of failed logins in the period
  • event_summary.total_successful — number of successful logins in the period
  • event_summary.total_fail_ratio — percent of failed logins in the period, which is: event_summary.total_failed / (event_summary.total_failed + event_summary.total_successful)
  • accumulated_anomalous_failures — score value of the model indicating the degree of abnormal activity
  • login_type — type of login, such as ssh_traffic, okta_log, or aws_cloudtrail
  • srcip_host — source host name
  • srcip_reputation — source reputation

Use Case with Data Points

Login failures and successes are calculated periodically for every source (srcip) and destination (dstip) IP address. If the number of failures is significantly larger than the number of successes, an alert is triggered. The Interflow includes the login type (login_type), source host (srcip_host), and source reputation (srcip_reputation).

External Brute-Forced Successful User Login

A successful login was observed from an IP address that had previously seen a large number of login failures, or a successful login to a user account was observed from another IP address or IP addresses that had previously seen a large number of login failures to that account. Check with the user.

This alert type has two subtypes:

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is external_user_success_brute_forcer.

Alert Subtype: Source IP-Based

The source IP-based alert subtype has the same XDR Kill Chain and Event Name as the user ID-based alert subtype, but differs in the Key Fields and Relevant Data Points and Use Case with Data Points.

Key Fields and Relevant Data Points

  • srcip — source IP address  
  • srcip_usersid — Windows SID associated with the source IP address
  • srcip_host — source host name
  • srcip_reputation — source reputation
  • source_geo.countryName — source country
  • dstip_host — destination host name
  • login_type — type of login
  • username — user name
  • related_alert._id — link to the related External User Login Failure Anomaly

Use Case with Data Points

The login records are checked for every external source IP address (srcip). An alert is triggered if that IP address:

  1. Has so many failed login attempts that it triggered the External User Login Failure Anomaly, and
  2. Had a successful login

A sample Interflow includes the source IP address (srcip), login type (login_type), source host (srcip_host), source reputation (srcip_reputation), source country (srcip_geo.countryName), and user name (username).

Alert Subtype: User ID-Based

The user ID-based alert subtype has the same XDR Kill Chain and Event Name as the source IP-based alert subtype, but differs in the Key Fields and Relevant Data Points and Use Case with Data Points.

Key Fields and Relevant Data Points

  • srcip_usersid — Windows SID associated with the source IP address 
  • srcip — source IP address
  • srcip_host — source host name
  • srcip_reputation — source reputation
  • source_geo.countryName — source country
  • dstip_host — destination host name
  • login_type — type of login
  • username — user name
  • related_alert._id — link to the related External Account Login Failure Anomaly

Use Case with Data Points

The login records to a user account (srcip_usersid) are checked for every external source IP address (srcip). An alert is triggered if that user account:

  1. Has so many failed login attempts that it triggered the External Account Login Failure Anomaly, and

  2. Had a successful login

A sample Interflow includes the source IP address (srcip), login type (login_type), source host (srcip_host), source reputation (srcip_reputation), source country (srcip_geo.countryName), and user name (username).

File Creation Anomaly

A file or files were created an anomalously large number of times. Check with the user to see if this is expected.

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: XDR EBA (XTA0001)

  • Technique: XDR File Anomaly (XT1003)

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is file_creation.

Key Fields and Relevant Data Points

  • secondary — user name  
  • actual — actual number of file creations in the period
  • typical — typical number of file creations in the period
  • path — path to the file(s) created

Use Case with Data Points

The number of file creations for each user (command) is calculated periodically. If the volume (actual) is much larger than the typical volume (typical) of file creations in any period, an alert is triggered. The Interflow includes the directory to the file (path).

Google Workspace Attack Warning

Attacks to a Google Workspace account were detected. Check with the account holder.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is gsuite_attack_warning.

Key Fields and Relevant Data Points

  • actor.email — key ID for the account  
  • srcip — source IP address
  • srcip_host — source host name
  • event_detail.nameGoogle Workspace suspicious event name
  • event_detail.typeGoogle Workspace suspicious event type

Use Case with Data Points

For each Google Workspace account (actor.email), attacks are searched periodically. If an attack is identified, an alert is triggered. The Interflow includes the account ID (actor.email), source IP address (srcip), Google Workspace event name (event_detail.name), and Google Workspace event type (event_detail.type).

Google Workspace Suspicious Activities

Suspicious activities were detected in a Google Workspace account. Check with the account holder.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Login Anomaly (XT4006)

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is gsuite_suspicious_activities.

Key Fields and Relevant Data Points

  • actor.email — key ID for the account  
  • srcip — source IP address
  • srcip_host — source host name
  • event_detail.nameGoogle Workspace suspicious event name
  • event_detail.typeGoogle Workspace suspicious event type

Use Case with Data Points

For each Google Workspace account (actor.email), suspicious activities are searched periodically. If suspicious activities are detected, an alert is triggered. The Interflow includes the account ID (actor.email), source IP address (srcip), Google Workspace event name (event_detail.name), and Google Workspace event type (event_detail.type).

Google Workspace Account Manipulation

A Google Workspace user was suspended for a suspicious reason or because a password leak was detected. Check with the user.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Account Anomaly (XT4007)

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is gsuite_account_manipulation.

Key Fields and Relevant Data Points

  • event_detail.affected_email_address — key ID for the account  
  • event_detail.nameGoogle Workspace suspicious event name
  • event_detail.typeGoogle Workspace suspicious event type

Use Case with Data Points

For each Google Workspace account (event_detail.affected_email_address), account manipulation is evaluated periodically. This alert is triggered if the Google Security center reports a leaked password or a user account being suspended for specific reasons. The Interflow includes the account ID (event_detail.affected_email_address), Google Workspace event name (event_detail.name), and Google Workspace event type (event_detail.type).

Google Workspace User Suspended

A Google Workspace user was suspended. Check with the user.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Account Anomaly (XT4007)

  • Tags: [External]

Event Name

The xdr_event.name for this alert type in the Interflow data is gsuite_user_suspended.

Key Fields and Relevant Data Points

  • actor.email — key ID for the account  
  • srcip — source IP address
  • srcip_host — source host name
  • event_detail.nameGoogle Workspace suspicious event name
  • event_detail.typeGoogle Workspace suspicious event type

Use Case with Data Points

For each Google Workspace account (actor.email), suspension status is searched periodically. If a user is suspended, an alert is triggered. The Interflow includes the account ID (actor.email), source IP address (srcip), Google Workspace event name (event_detail.name), and Google Workspace event type (event_detail.type).

Internal Account Login Failure Anomaly

An anomalously large number of login failures from an internal source IP address to an internal destination IP address was observed for an account. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Propagation

  • Tactic: [Internal] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [Internal]

Event Name

The xdr_event.name for this alert type in the Interflow data is internal_cloud_account_login_failure.

Key Fields and Relevant Data Points

  • srcip_usersid — account user ID  

    or

  • srcip_username — account user name, enriched from event_data.targetusername  

    The key field for this alert type can be either srcip_usersid or srcip_username, depending on the data feed.

  • event_summary.total_failed — number of failed logins in the period
  • event_summary.total_successful — number of successful logins in the period
  • event_summary.total_fail_ratio — percent of failed logins in the period, which is: event_summary.total_failed / (event_summary.total_failed + event_summary.total_successful)
  • accumulated_anomalous_failures — score value of the model indicating the degree of abnormal activity
  • srcip_host — host name of corresponding source IP address
  • login_type — type of login
  • srcip_reputation — source reputation

Use Case with Data Points

Login failures and successes between any internal IP addresses are calculated periodically for every account (srcip_usersid). If the number of failures is significantly larger than the number of successes, an alert is triggered. A sample Interflow includes the login type (login_type), source host (srcip_host), and source reputation (srcip_reputation).

Internal User Login Failure Anomaly

An anomalous number of login failures between internal IP addresses was observed for one of the following applications: SSH, SMTP, FTP, RDP, SMB, databases, Active Directory, Office 365, Okta, AWS CloudTrail, Google Workspace, Salesforce, or Microsoft Entra ID (formerly Azure AD). Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Propagation

  • Tactic: [Internal] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [Internal]

Event Name

The xdr_event.name for this alert type in the Interflow data is internal_user_login_fail.

Key Fields and Relevant Data Points

  • srcip — source IP address  
  • dstip — destination IP address  
  • dstip_host — destination host name
  • service_id — source domain, workstation, organization, or service
  • event_summary.total_failed — number of failed logins in the period
  • event_summary.total_successful — number of successful logins in the period
  • event_summary.total_fail_ratio — percent of failed logins in the period, which is: event_summary.total_failed / (event_summary.total_failed + event_summary.total_successful)
  • accumulated_anomalous_failures — score value of the model indicating the degree of abnormal activity
  • login_type — type of login, such as ssh_traffic, okta_log, or aws_cloudtrail
  • srcip_host — source host name
  • srcip_reputation — source reputation

Use Case with Data Points

Login failures and successes between internal IP addresses are calculated periodically for every source (srcip) and destination (dstip) IP address. If the number of failures is significantly larger than the number of successes, an alert is triggered. The Interflow includes the login type (login_type), source host (srcip_host), and source reputation (srcip_reputation).

Internal Brute-Forced Successful User Login

A successful login was observed from an IP address that had previously seen a large number of login failures, or a successful login to a user account was observed from another IP address or IP addresses that had previously seen a large number of login failures to that account. Check with the user.

This alert type has two subtypes:

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Propagation

  • Tactic: [Internal] Credential Access (TA0006 )

  • Technique: Brute Force (T1110 )

  • Tags: [Internal]

Event Name

The xdr_event.name for this alert type in the Interflow data is internal_user_success_brute_forcer.

Alert Subtype: Source IP-Based

The source IP-based alert subtype has the same XDR Kill Chain and Event Name as the user ID-based alert subtype, but differs in the Key Fields and Relevant Data Points and Use Case with Data Points.

Key Fields and Relevant Data Points

  • srcip — source IP address  
  • srcip_usersid — Windows SID associated with the source IP address
  • srcip_host — source host name
  • srcip_reputation — source reputation
  • source_geo.countryName — source country
  • dstip_host — destination host name
  • login_type — type of login
  • username — user name
  • related_alert._id — link to the related Internal User Login Failure Anomaly

Use Case with Data Points

The login records to an internal IP address (dstip) are checked for every internal source IP address (srcip). An alert is triggered if that IP address:

  1. Has so many failed login attempts that it triggered the Internal User Login Failure Anomaly, and

  2. Had a successful login

A sample Interflow includes the source IP address (srcip), login type (login_type), source host name (srcip_host), source reputation (srcip_reputation), source country (srcip_geo.countryName), and user name (username).

Alert Subtype: User ID-Based

The user ID-based alert subtype has the same XDR Kill Chain and Event Name as the source IP-based alert subtype, but differs in the Key Fields and Relevant Data Points and Use Case with Data Points.

Key Fields and Relevant Data Points

  • srcip — source IP address
  • srcip_usersid — Windows SID associated with the source IP address 
  • srcip_host — source host name
  • srcip_reputation — source reputation
  • source_geo.countryName — source country
  • dstip_host — destination host name
  • login_type — type of login
  • username — user name
  • related_alert._id — link to the related Internal Account Login Failure Anomaly

Use Case with Data Points

The login records to a user account (srcip_usersid) are checked for every internal source IP address (srcip). An alert is triggered if that user account:

  1. Has so many failed login attempts that it triggered the Internal Account Login Failure Anomaly, and

  2. Had a successful login

A sample Interflow includes the source IP address (srcip), login type (login_type), source host name (srcip_host), source reputation (srcip_reputation), source country (srcip_geo.countryName), and user name (username).

Uncommon Process Anomaly

An asset launched a process that has never been observed by Stellar Cyber (or been seen very rarely). This could indicate a malware attack.

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: XDR EBA (XTA0001)

  • Technique: XDR Process Anomaly (XT1001)

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is network_uncommon_process.

Key Fields and Relevant Data Points

  • process_name — name of the process  
  • days_silent — number of days since this process was last seen
  • srcip — source IP address running the process
  • process_user — name of the user running the process

Use Case with Data Points

If a process (process_name) has never been observed by Stellar Cyber or been seen very rarely (days_silent), an alert is triggered. The Interflow includes the user (process_user) and host (srcip) that executed the process.

Abnormal Parent / Child Process

A process that typically launches a small, consistent number of child processes launched a new child process. Investigate the child process to see if it is benign.

This alert type has two subtype categories:

Alert Subtype: Machine Learning Anomaly Detection

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: XDR EBA (XTA0001)

  • Technique: XDR Process Relationship Anomaly (XT1002)

  • Tags: []

Event Name

The xdr_event.name for this alert type in the Interflow data is parent_child.

Key Fields and Relevant Data Points

  • parent_proc_name — name of the parent process  
  • srcip_host — host name of corresponding source IP address
  • process_name — name of the process
  • stability — score measuring the time since the parent process launched the last child process
  • diversity — score measuring the number of child processes that the parent process spawned
  • days_stable — time since the parent process launched the last child process
  • child_count — number of child processes that the parent process spawned

Use Case with Data Points

Each pair of parent/child processes (parent_proc_name and process_name) is examined periodically. If a parent process (parent_proc_name) with a small number of child processes (diversity, child_count) has not launched a new child process (process_name) for a long time (stability, days_stable) launches a new child process from a host (srcip_host), an alert is triggered.

Alert Subtype: Rule Based Detection

The Parent/Child Suspicious Process Creation rules are used to identify suspicious activity with parent/child relationships associated with process creation. Any one or more of these will trigger the Parent/Child Suspicious Process Creation alert types.

Key Fields and Relevant Data Points

  • hostip — host IP address 
  • hostip_host — host name
  • stellar.rule_idStellar Cyber rule ID

Link to Rule-Based Alert Types

Rules Contributing to Parent/Child Suspicious Process Creation Alert Type

Impossible Travel Anomaly

A user logged in from locations that are geographically impossible to travel between in the time frame. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Location Anomaly (XT2001)

  • Tags: [User Behavior Analytics]

Event Name

The xdr_event.name for this alert type in the Interflow data is user_impossible_travel.

Key Fields and Relevant Data Points

  • srcip_usersid — source user ID  
  • srcip_username — source user name
  • srcip — source IP address
  • srcip_geo — source IP address geo location, including latitude and longitude
  • distance_deviation — deviation in distance (miles) between the two login locations
  • time_deviation — deviation in time (seconds) between the two login events
  • travel_speed — calculated speed for the user to travel between the two location (miles/hour)
  • appid_name — application name for the login event
  • last_login_time — time of 2nd login, event 2 (E2)
  • _id2 — ID of E2
  • _index2 — index of E2
  • srcip2 — source IP address of E2
  • srcip_geo2 — source IP address geo location of E2, including latitude and longitude
  • engid_gateway — gateway IP address, used to determine geo location when source IP address is private

Use Case with Data Points

Login events (E1 and E2) are examined for a user (srcip_usersid), to see if the login locations (srcip_geo and srcip_geo2), that are at least 100 miles apart, changed faster (travel_speed = distance_deviation/time_deviation) than possible with the typical commercial flight speed of 600 miles/hour.

E1 is the basis for the Interflow. The srcip_usersid and srcip_username identify the user, appid_name identifies the application, and last_login_time identifies the time when the 2nd login event happened. You can find detailed information about E2 by checking id2 in index2, source IP (srcip2), and geo location (srcip_geo2).

User Login Location Anomaly

A user logged in from an anomalous location. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Location Anomaly (XT2001)

  • Tags: [External; User Behavior Analytics]

Event Name

The xdr_event.name for this alert type in the Interflow data is user_login_region.

Key Fields and Relevant Data Points

  • srcip_usersid — source user ID  
  • distance_deviation — deviation in distance between two login locations (miles)
  • srcip_host — host name of corresponding source IP address
  • srcip_reputation — source reputation
  • srcip_geo.countryName — source country
  • srcip_geo.region — source region
  • srcip_geo.city — source city
  • dstip_host — host name of corresponding destination IP address
  • login_type — type of login

Use Case with Data Points

Successful login events for certain login types (login_type) of a user (srcip_usersid) from a source host (srcip_host) and country location (srcip_geo.countryName are examined. If the detected login location is too far away (distance_deviation in miles) from that user's typical locations, an alert is triggered. The source host's reputation (srcip_reputation) is also checked. Map views of the Interflow include data points for the closest typical login locations for the user.

Login Time Anomaly

A user logged in at an abnormal time. Check with the user.

This alert type has a relatively long detection delay of up to 40 minutes because it waits for login events from high latency data sources and is sensitive to the event order of user logins.

XDR Kill Chain

  • Kill Chain Stage: Initial Attempts

  • Tactic: [External] XDR UBA (XTA0004)

  • Technique: XDR Time Anomaly (XT4005)

  • Tags: [External; User Behavior Analytics]

Event Name

The xdr_event.name for this alert type in the Interflow data is user_login_time.

Key Fields and Relevant Data Points

  • srcip_usersid — source user ID  
  • srcip_username — source user name
  • srcip_host — host name of corresponding source IP address
  • srcip_geo.countryName — source country
  • dstip_host — host name of corresponding destination IP address
  • actual — actual login time
  • typical — typical login time
  • actual_range — actual login time range
  • typical_range — typical login time range

Use Case with Data Points

Every user's (srcip_usersid) login time (actual) is compared to the typical login times (typical_range). If it is outside the range, an alert is triggered. The Interflow includes information such as the source user name (srcip_username), source host name (srcip_host), and source country (srcip_geo.countryName), as well as the destination host (dstip_host).

User Process Usage Anomaly

A user who typically executes a small, consistent number of processes suddenly executed a new process. Investigate the process, to see if it is benign. Check with the user to see if this process was expected.

XDR Kill Chain

  • Kill Chain Stage: Persistent Foothold

  • Tactic: XDR EBA (XTA0001)

  • Technique: XDR Process Anomaly (XT1001)

  • Tags: [User Behavior Analytics]

Event Name

The xdr_event.name for this alert type in the Interflow data is user_uncommon_process.

Key Fields and Relevant Data Points

  • srcip_usersid — non-Windows source user ID  

    or

  • user.identifier — Windows source user ID  

    The key field for this alert type can be either srcip_usersid or user.identifier, depending on the data feed.

  • process_name — name of the process  
  • srcip_host — host name of corresponding source IP address
  • dstip_host — host name of corresponding destination IP address
  • srcip_username — source user name
  • stability — score measuring the time since the last new process was executed
  • diversity — score measuring the number of processes that the user executed
  • days_stable — time since the last new process was executed
  • child_count — number of processes that the user executed

Use Case with Data Points

Looks for a user (srcip_usersid or user.identifier and a srcip_username) with a small number of processes (diversity, child_count) who also has not used a new process for a long time (stability, days_stable). If a new process (process_name) appears on a host (srcip_host) with this user and connects to another host (dstip_host), an alert is triggered.

The user is identified with the scrip_userid or user.identifier and scrip_username fields. The process is identified with the process_name field. The host on which the user is running the process is identified with the srcip_host field. The destination of the traffic generated by the process is identified with the dstip_host field. Stability is identified with the stability field, and diversity is identified with the diversity field.