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Security anomaly detection configurations

These anomaly detection jobs automatically detect file system and network anomalies on your hosts. They appear in the Anomaly Detection interface of the Elastic Security app in Kibana when you have data that matches their configuration. For more information, refer to Anomaly detection with machine learning.

Note

In Elastic Stack 9.4, Entity Analytics introduces fields for entity resolution. The machine learning jobs created in this version and later are designed to leverage these fields.

  • The affected machine learning jobs include an _ea suffix in their names, as described in each module below.
  • Previously installed machine learning jobs and detection rules continue to run, allowing time to transition to the Entity Analytics fields.
  • We recommend that you install the _ea machine learning jobs and verify they are collecting data and generating anomalies before upgrading to the latest detection rules included in 9.4.

To use these anomaly detection jobs, install and configure one of the supported integrations listed in each job's table. No additional configuration is required beyond the integration's standard setup. For installation instructions, refer to each integration's documentation.

Detect anomalous activity in your ECS-compatible authentication logs.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

By default, when you create these jobs in the Elastic Security app, the job wizard uses a data view that applies to multiple indices. If you use Machine Learning instead, create a similar data view and select it in the job wizard so the results match.

auth_high_count_logon_events_ea

Looks for an unusually large spike in successful authentication events. This can be due to password spraying, user enumeration, or brute force activity.

Supported integrations: System, Elastic Defend, Winlogbeat, Windows

Supported OS: Windows

Job (JSON): code

Datafeed: code

auth_high_count_logon_events

Looks for an unusually large spike in successful authentication events. This can be due to password spraying, user enumeration, or brute force activity.

Supported integrations: System, Elastic Defend, Winlogbeat, Windows

Supported OS: Windows

Job (JSON): code

Datafeed: code

auth_high_count_logon_events_for_a_source_ip_ea

Looks for an unusually large spike in successful authentication events from a particular source IP address. This can be due to password spraying, user enumeration or brute force activity.

Supported integrations: System, Elastic Defend, Winlogbeat, Windows

Supported OS: Windows

Job (JSON): code

Datafeed: code

auth_high_count_logon_events_for_a_source_ip

Looks for an unusually large spike in successful authentication events from a particular source IP address. This can be due to password spraying, user enumeration or brute force activity.

Supported integrations: System, Elastic Defend, Winlogbeat, Windows

Supported OS: Windows

Job (JSON): code

Datafeed: code

auth_high_count_logon_fails_ea

Looks for an unusually large spike in authentication failure events. This can be due to password spraying, user enumeration, or brute force activity and may be a precursor to account takeover or credentialed access.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_high_count_logon_fails

Looks for an unusually large spike in authentication failure events. This can be due to password spraying, user enumeration, or brute force activity and may be a precursor to account takeover or credentialed access.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_hour_for_a_user_ea

Looks for a user logging in at a time of day that is unusual for the user. This can be due to credentialed access through a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_hour_for_a_user

Looks for a user logging in at a time of day that is unusual for the user. This can be due to credentialed access through a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_source_ip_for_a_user_ea

Looks for a user logging in from an IP address that is unusual for the user. This can be due to credentialed access through a compromised account when the user and the threat actor are in different locations. An unusual source IP address for a username could also be due to lateral movement when a compromised account is used to pivot between hosts.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_source_ip_for_a_user

Looks for a user logging in from an IP address that is unusual for the user. This can be due to credentialed access through a compromised account when the user and the threat actor are in different locations. An unusual source IP address for a username could also be due to lateral movement when a compromised account is used to pivot between hosts.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_user_ea

Looks for an unusual user name in the authentication logs. An unusual user name is one way of detecting credentialed access by means of a new or dormant user account. A user account that is normally inactive, because the user has left the organization, which becomes active, may be due to credentialed access using a compromised account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web application.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

auth_rare_user

Looks for an unusual user name in the authentication logs. An unusual user name is one way of detecting credentialed access by means of a new or dormant user account. A user account that is normally inactive, because the user has left the organization, which becomes active, may be due to credentialed access using a compromised account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web application.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

suspicious_login_activity_ea

Detect unusually high number of authentication attempts.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

suspicious_login_activity

Detect unusually high number of authentication attempts.

Supported integrations: System, Elastic Defend, Auditd Manager

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

Detect suspicious activity recorded in your Azure Activity Logs.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

azure_activitylogs_high_distinct_count_event_action_fail_ea

Looks for a spike in the rate of an error message, which might indicate an impending service failure or potentially be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_high_distinct_count_event_action_on_failure

Looks for a spike in the rate of an error message, which might indicate an impending service failure or potentially be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_on_failure_ea

Looks for unusual Azure activity event actions on failure. Rare and unusual errors might simply indicate an impending service failure but they can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_on_failure

Looks for unusual Azure activity event actions on failure. Rare and unusual errors might simply indicate an impending service failure but they can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_city_ea

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (city) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_city

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (city) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_country_ea

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (country) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_country

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (country) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_user_email_ea

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a unique user identifier context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

azure_activitylogs_rare_event_action_for_a_username

Looks for Azure activity event actions that, while not inherently suspicious or atypical, are sourcing from a user context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: Azure Activity Logs

Job (JSON): code

Datafeed: code

Detect suspicious activity recorded in your CloudTrail logs.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

high_distinct_count_error_message

Looks for a spike in the rate of an error message which may simply indicate an impending service failure but these can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

rare_error_code

Looks for unusual errors. Rare and unusual errors may simply indicate an impending service failure but they can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

rare_method_for_a_city

Looks for AWS API calls that, while not inherently suspicious or abnormal, are sourcing from a geolocation (city) that is unusual. This can be the result of compromised credentials or keys.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

rare_method_for_a_country

Looks for AWS API calls that, while not inherently suspicious or abnormal, are sourcing from a geolocation (country) that is unusual. This can be the result of compromised credentials or keys.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

rare_method_for_a_user_id_ea

Looks for AWS API calls that, while not inherently suspicious or atypical, are sourcing from a user context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

rare_method_for_a_username

Looks for AWS API calls that, while not inherently suspicious or atypical, are sourcing from a user context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: AWS

Job (JSON): code

Datafeed: code

Detect suspicious activity recorded in your GCP Audit logs.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

Note

Entity Analytics machine learning jobs require GCP Audit integration version 2.47.2 or later.

gcp_audit_high_distinct_count_error_message_ea

Looks for a spike in the rate of an action where the event outcome is a failure. Spikes might indicate an impending service failure but could also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_high_distinct_count_error_message

Looks for a spike in the rate of an action where the event outcome is a failure. Spikes might indicate an impending service failure but could also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_error_code_ea

Looks for unusual errors. Rare and unusual errors might indicate an impending service failure but they can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_error_code

Looks for unusual errors. Rare and unusual errors might indicate an impending service failure but they can also be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection activity by a threat actor.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_city_ea

Looks for GCP actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (city) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_city

Looks for GCP actions that, while not inherently suspicious or atypical, are sourcing from a geolocation (city) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_country_ea

Looks for GCP actions calls that, while not inherently suspicious or atypical, are sourcing from a geolocation (country) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_country

Looks for GCP actions calls that, while not inherently suspicious or atypical, are sourcing from a geolocation (country) that is unexpected. This can be the result of compromised credentials or keys.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_user_email_ea

Looks for GCP actions that, while not inherently suspicious or atypical, are sourcing from a user context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

gcp_audit_rare_method_for_a_client_user_email

Looks for GCP actions that, while not inherently suspicious or atypical, are sourcing from a user context that does not normally call the method. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfil data.

Supported integrations: GCP Audit

Job (JSON): code

Datafeed: code

Anomaly detection jobs for host-based threat hunting and detection.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

To access the host traffic anomalies dashboard in Kibana, go to: Security -> Dashboards -> Host Traffic Anomalies.

high_count_events_for_a_host_name_ea

Detects sudden spikes in traffic associated with a host. This can be due to a range of security issues, such as a compromised system, DDoS attacks, malware infections, privilege escalation, or data exfiltration.

Supported integrations: Windows, Elastic Defend, Network Packet Capture, Auditd Manager, System

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

high_count_events_for_a_host_name

Looks for a sudden spike in host based traffic. This can be due to a range of security issues, such as a compromised system, DDoS attacks, malware infections, privilege escalation, or data exfiltration.

Supported integrations: Windows, Elastic Defend, Network Packet Capture, Auditd Manager, System

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

low_count_events_for_a_host_name_ea

Detects sudden drops in traffic associated with a host. This can be due to a range of security issues, such as a compromised system, a failed service, or a network misconfiguration.

Supported integrations: Windows, Elastic Defend, Network Packet Capture, Auditd Manager, System

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

low_count_events_for_a_host_name

Looks for a sudden drop in host based traffic. This can be due to a range of security issues, such as a compromised system, a failed service, or a network misconfiguration.

Supported integrations: Windows, Elastic Defend, Network Packet Capture, Auditd Manager, System

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

Anomaly detection jobs for Linux host-based threat hunting and detection.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

v3_linux_anomalous_network_activity_ea

Looks for unusual processes using the network which could indicate command-and-control, lateral movement, persistence, or data exfiltration activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_network_activity

Looks for unusual processes using the network which could indicate command-and-control, lateral movement, persistence, or data exfiltration activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_network_port_activity_ea

Looks for unusual destination port activity that could indicate command-and-control, persistence mechanism, or data exfiltration activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_network_port_activity

Looks for unusual destination port activity that could indicate command-and-control, persistence mechanism, or data exfiltration activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_process_all_hosts_ea

Looks for processes that are unusual to all Linux hosts. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_process_all_hosts

Looks for processes that are unusual to all Linux hosts. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_user_name_ea

Rare and unusual users that are not normally active may indicate unauthorized changes or activity by an unauthorized user which may be credentialed access or lateral movement.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_anomalous_user_name

Rare and unusual users that are not normally active may indicate unauthorized changes or activity by an unauthorized user which may be credentialed access or lateral movement.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_network_configuration_discovery_ea

Looks for commands related to system network configuration discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network configuration discovery to increase their understanding of connected networks and hosts. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_network_configuration_discovery

Looks for commands related to system network configuration discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network configuration discovery to increase their understanding of connected networks and hosts. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_network_connection_discovery_ea

Looks for commands related to system network connection discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network connection discovery to increase their understanding of connected services and systems. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_network_connection_discovery

Looks for commands related to system network connection discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network connection discovery to increase their understanding of connected services and systems. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_metadata_process_ea

Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_metadata_process

Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_metadata_user_ea

Looks for anomalous access to the metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_metadata_user

Looks for anomalous access to the metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_sudo_user_ea

Looks for sudo activity from an unusual user context. Unusual user context changes can be due to privilege escalation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_sudo_user

Looks for sudo activity from an unusual user context. Unusual user context changes can be due to privilege escalation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_user_compiler_ea

Looks for compiler activity by a user context which does not normally run compilers. This can be ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation through locally run exploits or malware activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_rare_user_compiler

Looks for compiler activity by a user context which does not normally run compilers. This can be ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation through locally run exploits or malware activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_information_discovery_ea

Looks for commands related to system information discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system information discovery to gather detailed information about system configuration and software versions. This may be a precursor to the selection of a persistence mechanism or a method of privilege elevation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_information_discovery

Looks for commands related to system information discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system information discovery to gather detailed information about system configuration and software versions. This may be a precursor to the selection of a persistence mechanism or a method of privilege elevation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_process_discovery_ea

Looks for commands related to system process discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system process discovery to increase their understanding of software applications running on a target host or network. This may be a precursor to the selection of a persistence mechanism or a method of privilege elevation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_process_discovery

Looks for commands related to system process discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system process discovery to increase their understanding of software applications running on a target host or network. This may be a precursor to the selection of a persistence mechanism or a method of privilege elevation.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_user_discovery_ea

Looks for commands related to system user or owner discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system owner or user discovery to identify currently active or primary users of a system. This may be a precursor to additional discovery, credential dumping, or privilege elevation activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_linux_system_user_discovery

Looks for commands related to system user or owner discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system owner or user discovery to identify currently active or primary users of a system. This may be a precursor to additional discovery, credential dumping, or privilege elevation activity.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_rare_process_by_host_linux_ea

Looks for processes that are unusual to a particular Linux host. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

v3_rare_process_by_host_linux

Looks for processes that are unusual to a particular Linux host. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Network Packet Capture, Auditd Manager, Packetbeat

Supported OS: Linux

Job (JSON): code

Datafeed: code

Detect anomalous network activity in your ECS-compatible network logs.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

By default, when you create these jobs in the Elastic Security app, the job wizard uses a data view that applies to multiple indices. If you use Machine Learning instead, create a similar data view and select it in the job wizard so the results match.

high_count_by_destination_country

Looks for an unusually large spike in network activity to one destination country in the network logs. This could be due to unusually large amounts of reconnaissance or enumeration traffic. Data exfiltration activity may also produce such a surge in traffic to a destination country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

high_count_network_denies

Looks for an unusually large spike in network traffic that was denied by network ACLs or firewall rules. Such a burst of denied traffic is usually either 1) a misconfigured application or firewall or 2) suspicious or malicious activity. Unsuccessful attempts at network transit, in order to connect to command-and-control (C2), or engage in data exfiltration, may produce a burst of failed connections. This could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

high_count_network_events

Looks for an unusually large spike in network traffic. Such a burst of traffic, if not caused by a surge in business activity, can be due to suspicious or malicious activity. Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

rare_destination_country

Looks for an unusual destination country name in the network logs. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from a server in a country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux, macOS

Job (JSON): code

Datafeed: code

Detect suspicious network activity in Packetbeat data.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

packetbeat_dns_tunneling_ea

Looks for unusual DNS activity that could indicate command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_dns_tunneling

Looks for unusual DNS activity that could indicate command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_dns_question_ea

Looks for unusual DNS activity that could indicate command-and-control activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_dns_question

Looks for unusual DNS activity that could indicate command-and-control activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_server_domain_ea

Looks for unusual HTTP or TLS destination domain activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_server_domain

Looks for unusual HTTP or TLS destination domain activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_urls_ea

Looks for unusual web browsing URL activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_urls

Looks for unusual web browsing URL activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_user_agent_ea

Looks for unusual HTTP user agent activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

packetbeat_rare_user_agent

Looks for unusual HTTP user agent activity that could indicate execution, persistence, command-and-control or data exfiltration activity.

Supported integrations: Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

Job (JSON): code

Datafeed: code

Anomaly detection jobs for Windows host-based threat hunting and detection.

In the Machine Learning app, these configurations are available only when data exists that matches the query specified in the manifest file. In the Elastic Security app, it looks in the data view specified in the securitySolution:defaultIndex advanced setting for data that matches the query.

If there are additional requirements such as installing the Windows System Monitor (Sysmon) or auditing process creation in the Windows security event log, they are listed for each job.

v3_rare_process_by_host_windows_ea

Looks for processes that are unusual to a particular Windows host. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_rare_process_by_host_windows

Looks for processes that are unusual to a particular Windows host. Such unusual processes may indicate unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_network_activity_ea

Looks for unusual processes using the network which could indicate command-and-control, lateral movement, persistence, or data exfiltration activity.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_network_activity

Looks for unusual processes using the network which could indicate command-and-control, lateral movement, persistence, or data exfiltration activity.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_path_activity_ea

Looks for activity in unusual paths that may indicate execution of malware or persistence mechanisms. Windows payloads often execute from user profile paths.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_path_activity

Looks for activity in unusual paths that may indicate execution of malware or persistence mechanisms. Windows payloads often execute from user profile paths.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_process_all_hosts_ea

Looks for processes that are unusual to all Windows hosts. Such unusual processes may indicate execution of unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_process_all_hosts

Looks for processes that are unusual to all Windows hosts. Such unusual processes may indicate execution of unauthorized software, malware, or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_process_creation_ea

Looks for unusual process relationships which may indicate execution of malware or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_process_creation

Looks for unusual process relationships which may indicate execution of malware or persistence mechanisms.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_script_ea

Looks for unusual powershell scripts that may indicate execution of malware, or persistence mechanisms.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_script

Looks for unusual powershell scripts that may indicate execution of malware, or persistence mechanisms.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_service_ea

Looks for rare and unusual Windows service names which may indicate execution of unauthorized services, malware, or persistence mechanisms.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_service

Looks for rare and unusual Windows service names which may indicate execution of unauthorized services, malware, or persistence mechanisms.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_user_name_ea

Rare and unusual users that are not normally active may indicate unauthorized changes or activity by an unauthorized user which may be credentialed access or lateral movement.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_anomalous_user_name

Rare and unusual users that are not normally active may indicate unauthorized changes or activity by an unauthorized user which may be credentialed access or lateral movement.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_metadata_process_ea

Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_metadata_process

Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_metadata_user_ea

Looks for anomalous access to the metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_metadata_user

Looks for anomalous access to the metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_user_runas_event_ea

Unusual user context switches can be due to privilege escalation.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_user_runas_event

Unusual user context switches can be due to privilege escalation.

Supported integrations: Elastic Defend, Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_user_type10_remote_login_ea

Unusual RDP (remote desktop protocol) user logins can indicate account takeover or credentialed access.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_user_type10_remote_login

Unusual RDP (remote desktop protocol) user logins can indicate account takeover or credentialed access.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_script_ea

Looks for rare powershell scripts that may indicate execution of malware, or persistence mechanisms using hash.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

v3_windows_rare_script

Looks for rare powershell scripts that may indicate execution of malware, or persistence mechanisms using hash.

Supported integrations: Windows, Winlogbeat

Supported OS: Windows

Job (JSON): code

Datafeed: code

Elastic Integrations are a streamlined way to add Elastic assets to your environment, such as data ingestion, transforms, and in this case, machine learning capabilities for Security.

The following Integrations use machine learning to analyze patterns of user and entity behavior, and help detect and alert when there is related suspicious activity in your environment.

Machine learning package to detect data exfiltration in your network and file data. Refer to the subscription page to learn more about the required subscription.

To download, refer to the documentation.

ded_high_sent_bytes_destination_geo_country_iso_code_ea

Detects data exfiltration to an unusual geo-location (by country iso code).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_geo_country_iso_code

Detects data exfiltration to an unusual geo-location (by country iso code).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_ip_ea

Detects data exfiltration to an unusual geo-location (by IP address).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_ip

Detects data exfiltration to an unusual geo-location (by IP address).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_port_ea

Detects data exfiltration to an unusual destination port.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_port

Detects data exfiltration to an unusual destination port.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_region_name_ea

Detects data exfiltration to an unusual geo-location (by region name).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_sent_bytes_destination_region_name

Detects data exfiltration to an unusual geo-location (by region name).

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

ded_high_bytes_written_to_external_device_ea

Detects data exfiltration activity by identifying high bytes written to an external device.

Supported integrations: Elastic Defend

Supported OS: Windows

ded_high_bytes_written_to_external_device

Detects data exfiltration activity by identifying high bytes written to an external device.

Supported integrations: Elastic Defend

Supported OS: Windows

ded_rare_process_writing_to_external_device_ea

Detects data exfiltration activity by identifying a file write started by a rare process to an external device.

Supported integrations: Elastic Defend

Supported OS: Windows

ded_rare_process_writing_to_external_device

Detects data exfiltration activity by identifying a file write started by a rare process to an external device.

Supported integrations: Elastic Defend

Supported OS: Windows

ded_high_bytes_written_to_external_device_airdrop_ea

Detects data exfiltration activity by identifying high bytes written to an external device using Airdrop.

Supported integrations: Elastic Defend

Supported OS: macOS

ded_high_bytes_written_to_external_device_airdrop

Detects data exfiltration activity by identifying high bytes written to an external device using Airdrop.

Supported integrations: Elastic Defend

Supported OS: macOS

The job configurations and datafeeds can be found here.

Machine learning solution package to detect domain generation algorithm (DGA) activity in your network data. Refer to the subscription page to learn more about the required subscription.

To download, refer to the documentation.

dga_high_sum_probability_ea

Detect domain generation algorithm (DGA) activity in your network data.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

dga_high_sum_probability

Detect domain generation algorithm (DGA) activity in your network data.

Supported integrations: Elastic Defend, Network Packet Capture, Packetbeat

Supported OS: Windows, Linux

The job configurations and datafeeds can be found here.

Machine learning package to detect lateral movement based on file transfer activity and Windows RDP events. Refer to the subscription page to learn more about the required subscription.

To download, refer to the documentation.

lmd_high_count_remote_file_transfer_ea

Detects unusually high file transfers to a remote host in the network.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_high_count_remote_file_transfer

Detects unusually high file transfers to a remote host in the network.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_high_file_size_remote_file_transfer_ea

Detects unusually high size of files shared with a remote host in the network.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_high_file_size_remote_file_transfer

Detects unusually high size of files shared with a remote host in the network.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_rare_file_extension_remote_transfer_ea

Detects data exfiltration to an unusual destination port.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_rare_file_extension_remote_transfer

Detects data exfiltration to an unusual destination port.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_rare_file_path_remote_transfer_ea

Detects unusual folders and directories on which a file is transferred.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_rare_file_path_remote_transfer

Detects unusual folders and directories on which a file is transferred.

Supported integrations: Elastic Defend

Supported OS: Windows, Linux

lmd_high_mean_rdp_session_duration_ea

Detects unusually high mean of RDP session duration.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_mean_rdp_session_duration

Detects unusually high mean of RDP session duration.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_var_rdp_session_duration_ea

Detects unusually high variance in RDP session duration.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_var_rdp_session_duration

Detects unusually high variance in RDP session duration.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_sum_rdp_number_of_processes_ea

Detects unusually high number of processes started in a single RDP session.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_sum_rdp_number_of_processes

Detects unusually high number of processes started in a single RDP session.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_unusual_time_weekday_rdp_session_start_ea

Detects an RDP session started at an unusual time or weekday.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_unusual_time_weekday_rdp_session_start

Detects an RDP session started at an unusual time or weekday.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_rdp_distinct_count_source_ip_for_destination_ea

Detects a high count of source IPs making an RDP connection with a single destination IP.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_rdp_distinct_count_source_ip_for_destination

Detects a high count of source IPs making an RDP connection with a single destination IP.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_rdp_distinct_count_destination_ip_for_source_ea

Detects a high count of destination IPs establishing an RDP connection with a single source IP.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_rdp_distinct_count_destination_ip_for_source

Detects a high count of destination IPs establishing an RDP connection with a single source IP.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_mean_rdp_process_args_ea

Detects unusually high number of process arguments in an RDP session.

Supported integrations: Elastic Defend

Supported OS: Windows

lmd_high_mean_rdp_process_args

Detects unusually high number of process arguments in an RDP session.

Supported integrations: Elastic Defend

Supported OS: Windows

The job configurations and datafeeds can be found here.

Machine learning solution package to detect Living off the Land (LotL) attacks in your environment. Refer to the subscription page to learn more about the required subscription. (Also known as ProblemChild).

To download, refer to the documentation.

problem_child_rare_process_by_host_ea

Looks for a process that has been classified as malicious on a host that does not commonly manifest malicious process activity.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_rare_process_by_host

Looks for a process that has been classified as malicious on a host that does not commonly manifest malicious process activity.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_host_ea

Looks for a set of one or more malicious child processes on a single host.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_host

Looks for a set of one or more malicious child processes on a single host.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_rare_process_by_user_ea

Looks for a process that has been classified as malicious where the user context is unusual and does not commonly manifest malicious process activity.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_rare_process_by_user

Looks for a process that has been classified as malicious where the user context is unusual and does not commonly manifest malicious process activity.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_rare_process_by_parent_ea

Looks for rare malicious child processes spawned by a parent process.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_rare_process_by_parent

Looks for rare malicious child processes spawned by a parent process.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_user_ea

Looks for a set of one or more malicious processes, started by the same user.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_user

Looks for a set of one or more malicious processes, started by the same user.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_parent_ea

Looks for a set of one or more malicious child processes spawned by the same parent process.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

problem_child_high_sum_by_parent

Looks for a set of one or more malicious child processes spawned by the same parent process.

Supported integrations: Elastic Defend, Windows

Supported OS: Windows

The job configurations and datafeeds can be found here.

Machine learning package to detect anomalous privileged access activity in Windows, Linux and Okta logs. Refer to the subscription page to learn more about the required subscription.

To download, refer to the documentation.

pad_windows_high_count_special_logon_events_ea

Detects unusually high special logon events initiated by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_high_count_special_privilege_use_events_ea

Detects unusually high special privilege use events initiated by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_high_count_group_management_events_ea

Detects unusually high security group management events initiated by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_high_count_user_account_management_events_ea

Detects unusually high security user account management events initiated by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_rare_privilege_assigned_to_user_ea

Detects an unusual privilege type assigned to a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_rare_group_name_by_user_ea

Detects an unusual group name accessed by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_rare_device_by_user_ea

Detects an unusual device accessed by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_rare_source_ip_by_user_ea

Detects an unusual source IP address accessed by a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_windows_rare_region_name_by_user_ea

Detects an unusual region name for a user.

Supported integrations: Elastic Defend

Supported OS: Windows

pad_linux_high_count_privileged_process_events_by_user_ea

Detects a spike in privileged commands executed by a user.

Supported integrations: Elastic Defend

Supported OS: Linux

pad_linux_rare_process_executed_by_user_ea

Detects a rare process executed by a user.

Supported integrations: Elastic Defend

Supported OS: Linux

pad_linux_high_median_process_command_line_entropy_by_user_ea

Detects process command lines executed by a user with an abnormally high median entropy value.

Supported integrations: Elastic Defend

Supported OS: Linux

pad_okta_spike_in_group_membership_changes_ea

Detects spike in group membership change events by a user.

Supported integrations: Okta

pad_okta_spike_in_user_lifecycle_management_changes_ea

Detects spike in user lifecycle management change events by a user.

Supported integrations: Okta

pad_okta_spike_in_group_privilege_changes_ea

Detects spike in group privilege change events by a user.

Supported integrations: Okta

pad_okta_spike_in_group_application_assignment_change_ea

Detects spike in group application assignment change events by a user.

Supported integrations: Okta

pad_okta_spike_in_group_lifecycle_changes_ea

Detects spike in group lifecycle change events by a user.

Supported integrations: Okta

pad_okta_high_sum_concurrent_sessions_by_user_ea

Detects an unusual sum of active sessions started by a user.

Supported integrations: Okta

pad_okta_rare_source_ip_by_user_ea

Detects an unusual source IP address accessed by a user.

Supported integrations: Okta

pad_okta_rare_region_name_by_user_ea

Detects an unusual region name for a user.

Supported integrations: Okta

pad_okta_rare_host_name_by_user_ea

Detects an unusual host name for a user.

Supported integrations: Okta

The job configurations and datafeeds can be found here.