diff --git a/reference/data-analysis/machine-learning/ootb-ml-jobs-siem.md b/reference/data-analysis/machine-learning/ootb-ml-jobs-siem.md index d6638e173e..0d96ad1fbf 100644 --- a/reference/data-analysis/machine-learning/ootb-ml-jobs-siem.md +++ b/reference/data-analysis/machine-learning/ootb-ml-jobs-siem.md @@ -26,15 +26,15 @@ In the {{ml-app}} app, these configurations are available only when data exists By default, when you create these job in the {{security-app}}, it uses a {{data-source}} that applies to multiple indices. To get the same results if you use the {{ml-app}} app, create a similar [{{data-source}}](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/manifest.json#L7) then select it in the job wizard. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_events.json) | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_events.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_events_for_a_source_ip.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_events_for_a_source_ip.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_fails.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_fails.json)| -| 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 via 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_hour_for_a_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_hour_for_a_user.json)| -| 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 via 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_source_ip_for_a_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_source_ip_for_a_user.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_user.json)| -| suspicious_login_activity | Detect unusually high number of authentication attempts. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/suspicious_login_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_suspicious_login_activity.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_events.json) | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_events.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat/), [Windows](https://www.elastic.co/docs/reference/integrations/windows) | windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_events_for_a_source_ip.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_events_for_a_source_ip.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat), [Windows](https://www.elastic.co/docs/reference/integrations/windows) | windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_high_count_logon_fails.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_high_count_logon_fails.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager) | windows, linux | +| 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 via 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_hour_for_a_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_hour_for_a_user.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager) | windows, linux | +| 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 via 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_source_ip_for_a_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_source_ip_for_a_user.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager) | windows, linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/auth_rare_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_auth_rare_user.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager) | windows, linux | +| suspicious_login_activity | Detect unusually high number of authentication attempts. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/suspicious_login_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_auth/ml/datafeed_suspicious_login_activity.json)| [System](https://www.elastic.co/docs/reference/integrations/system), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager) | windows, linux | ## Security: CloudTrail [security-cloudtrail-jobs] @@ -43,13 +43,13 @@ Detect suspicious activity recorded in your CloudTrail logs. In the {{ml-app}} app, these configurations are available only when data exists that matches the query specified in the [manifest file](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/manifest.json). In the {{security-app}}, it looks in the {{data-source}} specified in the [`securitySolution:defaultIndex` advanced setting](kibana://reference/advanced-settings.md#securitysolution-defaultindex) for data that matches the query. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/high_distinct_count_error_message.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_high_distinct_count_error_message.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_error_code.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_error_code.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_city.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_city.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_country.json)| -| rare_method_for_a_username | Looks for AWS API calls that, while not inherently suspicious or abnormal, 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_username.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_username.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/high_distinct_count_error_message.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_high_distinct_count_error_message.json)| [AWS](https://www.elastic.co/docs/reference/integrations/aws/cloudtrail) | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_error_code.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_error_code.json)| [AWS](https://www.elastic.co/docs/reference/integrations/aws/cloudtrail) | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_city.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_city.json)| [AWS](https://www.elastic.co/docs/reference/integrations/aws/cloudtrail) | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_country.json)| [AWS](https://www.elastic.co/docs/reference/integrations/aws/cloudtrail) | +| rare_method_for_a_username | Looks for AWS API calls that, while not inherently suspicious or abnormal, 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/rare_method_for_a_username.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_cloudtrail/ml/datafeed_rare_method_for_a_username.json)| [AWS](https://www.elastic.co/docs/reference/integrations/aws/cloudtrail) | ## Security: Host [security-host-jobs] @@ -60,10 +60,10 @@ In the {{ml-app}} app, these configurations are available only when data exists To access the host traffic anomalies dashboard in Kibana, go to: `Security -> Dashboards -> Host Traffic Anomalies`. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/high_count_events_for_a_host_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/datafeed_high_count_events_for_a_host_name.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/low_count_events_for_a_host_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/datafeed_low_count_events_for_a_host_name.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/high_count_events_for_a_host_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/datafeed_high_count_events_for_a_host_name.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [System](https://www.elastic.co/docs/reference/integrations/system) | windows, linux, macOS | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/low_count_events_for_a_host_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_host/ml/datafeed_low_count_events_for_a_host_name.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [System](https://www.elastic.co/docs/reference/integrations/system) | windows, linux, macOS | ## Security: Linux [security-linux-jobs] @@ -72,22 +72,22 @@ Anomaly detection jobs for Linux host-based threat hunting and detection. In the {{ml-app}} app, these configurations are available only when data exists that matches the query specified in the [manifest file](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/manifest.json). In the {{security-app}}, it looks in the {{data-source}} specified in the [`securitySolution:defaultIndex` advanced setting](kibana://reference/advanced-settings.md#securitysolution-defaultindex) for data that matches the query. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_network_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_network_activity.json)| -| v3_linux_anomalous_network_port_activity | Looks for unusual destination port activity that could indicate command-and-control, persistence mechanism, or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_network_port_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_network_port_activity.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_process_all_hosts.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_process_all_hosts.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_user_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_user_name.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_network_configuration_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_network_configuration_discovery.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_network_connection_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_network_connection_discovery.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_metadata_process.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_metadata_process.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_metadata_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_metadata_user.json)| -| v3_linux_rare_sudo_user | Looks for sudo activity from an unusual user context. Unusual user context changes can be due to privilege escalation. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_sudo_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/securiity_linux/ml/datafeed_v3_linux_rare_sudo_user.json)| -| 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 via locally run exploits or malware activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_user_compiler.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_user_compiler.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_information_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_information_discovery.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_process_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_process_discovery.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_user_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_user_discovery.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_rare_process_by_host_linux.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_rare_process_by_host_linux.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_network_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_network_activity.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| v3_linux_anomalous_network_port_activity | Looks for unusual destination port activity that could indicate command-and-control, persistence mechanism, or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_network_port_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_network_port_activity.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_process_all_hosts.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_process_all_hosts.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_anomalous_user_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_anomalous_user_name.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_network_configuration_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_network_configuration_discovery.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_network_connection_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_network_connection_discovery.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_metadata_process.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_metadata_process.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_metadata_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_metadata_user.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| v3_linux_rare_sudo_user | Looks for sudo activity from an unusual user context. Unusual user context changes can be due to privilege escalation. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_sudo_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/securiity_linux/ml/datafeed_v3_linux_rare_sudo_user.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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 via locally run exploits or malware activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_rare_user_compiler.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_rare_user_compiler.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_information_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_information_discovery.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_process_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_process_discovery.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_linux_system_user_discovery.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_linux_system_user_discovery.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/v3_rare_process_by_host_linux.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_linux/ml/datafeed_v3_rare_process_by_host_linux.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Auditd Manager](https://www.elastic.co/docs/reference/integrations/auditd_manager), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | linux | ## Security: Network [security-network-jobs] @@ -98,12 +98,12 @@ In the {{ml-app}} app, these configurations are available only when data exists By default, when you create these jobs in the {{security-app}}, it uses a {{data-source}} that applies to multiple indices. To get the same results if you use the {{ml-app}} app, create a similar [{{data-source}}](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/manifest.json#L7) then select it in the job wizard. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_by_destination_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_by_destination_country.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_network_denies.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_network_denies.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_network_events.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_network_events.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/rare_destination_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_rare_destination_country.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_by_destination_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_by_destination_country.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux, macOS | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_network_denies.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_network_denies.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux, macOS | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/high_count_network_events.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_high_count_network_events.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux, macOS | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/rare_destination_country.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_network/ml/datafeed_rare_destination_country.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux, macOS | ## Security: {{packetbeat}} [security-packetbeat-jobs] @@ -112,13 +112,13 @@ Detect suspicious network activity in {{packetbeat}} data. In the {{ml-app}} app, these configurations are available only when data exists that matches the query specified in the [manifest file](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/manifest.json). In the {{security-app}}, it looks in the {{data-source}} specified in the [`securitySolution:defaultIndex` advanced setting](kibana://reference/advanced-settings.md#securitysolution-defaultindex) for data that matches the query. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| packetbeat_dns_tunneling | Looks for unusual DNS activity that could indicate command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_dns_tunneling.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_dns_tunneling.json)| -| packetbeat_rare_dns_question | Looks for unusual DNS activity that could indicate command-and-control activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_dns_question.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_dns_question.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_server_domain.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_server_domain.json)| -| packetbeat_rare_urls | Looks for unusual web browsing URL activity that could indicate execution, persistence, command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_urls.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_urls.json)| -| packetbeat_rare_user_agent | Looks for unusual HTTP user agent activity that could indicate execution, persistence, command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_user_agent.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_user_agent.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| packetbeat_dns_tunneling | Looks for unusual DNS activity that could indicate command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_dns_tunneling.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_dns_tunneling.json)| [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | +| packetbeat_rare_dns_question | Looks for unusual DNS activity that could indicate command-and-control activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_dns_question.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_dns_question.json)| [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) |windows, linux | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_server_domain.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_server_domain.json)| [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat)|windows, linux | +| packetbeat_rare_urls | Looks for unusual web browsing URL activity that could indicate execution, persistence, command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_urls.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_urls.json)| [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) |windows, linux | +| packetbeat_rare_user_agent | Looks for unusual HTTP user agent activity that could indicate execution, persistence, command-and-control or data exfiltration activity. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/packetbeat_rare_user_agent.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_packetbeat/ml/datafeed_packetbeat_rare_user_agent.json)| [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) |windows, linux | ## Security: Windows [security-windows-jobs] @@ -129,21 +129,21 @@ In the {{ml-app}} app, these configurations are available only when data exists 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. -| Name | Description | Job (JSON) | Datafeed | -| --- | --- | --- | --- | -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_rare_process_by_host_windows.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_rare_process_by_host_windows.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_network_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_network_activity.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_path_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_path_activity.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_process_all_hosts.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_process_all_hosts.json)| -| v3_windows_anomalous_process_creation | Looks for unusual process relationships which may indicate execution of malware or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_process_creation.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_process_creation.json)| -| v3_windows_anomalous_script | Looks for unusual powershell scripts that may indicate execution of malware, or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_script.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_script.json)| -| v3_windows_anomalous_service | Looks for rare and unusual Windows service names which may indicate execution of unauthorized services, malware, or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_service.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_service.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_user_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_user_name.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_metadata_process.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_metadata_process.json)| -| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_metadata_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_metadata_user.json)| -| v3_windows_rare_user_runas_event | Unusual user context switches can be due to privilege escalation. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_user_runas_event.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_user_runas_event.json)| -| v3_windows_rare_user_type10_remote_login | Unusual RDP (remote desktop protocol) user logins can indicate account takeover or credentialed access. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_user_type10_remote_login.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_user_type10_remote_login.json)| -| v3_windows_rare_script | Looks for rare powershell scripts that may indicate execution of malware, or persistence mechanisms via hash. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_script.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_script.json)| +| Name | Description | Job (JSON) | Datafeed | Supported Integrations | Supported OS | +| --- | --- | --- | --- |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| --- | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_rare_process_by_host_windows.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_rare_process_by_host_windows.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) | windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_network_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_network_activity.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_path_activity.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_path_activity.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_process_all_hosts.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_process_all_hosts.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| v3_windows_anomalous_process_creation | Looks for unusual process relationships which may indicate execution of malware or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_process_creation.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_process_creation.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| v3_windows_anomalous_script | Looks for unusual powershell scripts that may indicate execution of malware, or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_script.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_script.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) | windows | +| v3_windows_anomalous_service | Looks for rare and unusual Windows service names which may indicate execution of unauthorized services, malware, or persistence mechanisms. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_service.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_service.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_anomalous_user_name.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_anomalous_user_name.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_metadata_process.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_metadata_process.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| 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. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_metadata_user.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_metadata_user.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| v3_windows_rare_user_runas_event | Unusual user context switches can be due to privilege escalation. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_user_runas_event.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_user_runas_event.json)| [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| v3_windows_rare_user_type10_remote_login | Unusual RDP (remote desktop protocol) user logins can indicate account takeover or credentialed access. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_user_type10_remote_login.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_user_type10_remote_login.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | +| v3_windows_rare_script | Looks for rare powershell scripts that may indicate execution of malware, or persistence mechanisms via hash. | [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/v3_windows_rare_script.json)| [code](https://github.com/elastic/kibana/blob/main/x-pack/platform/plugins/shared/ml/server/models/data_recognizer/modules/security_windows/ml/datafeed_v3_windows_rare_script.json)| [Windows](https://www.elastic.co/docs/reference/integrations/windows), [Winlogbeat](https://www.elastic.co/docs/reference/beats/winlogbeat) |windows | ## Security: Elastic Integrations [security-integrations-jobs] @@ -163,9 +163,9 @@ The following Integrations use {{ml}} to analyze patterns of user and entity beh To download, refer to the [documentation](integration-docs://reference/dga/index.md). -| Name | Description | -| --- | --- | -| dga_high_sum_probability | Detect domain generation algorithm (DGA) activity in your network data. | +| Name | Description | Supported Integrations | Supported OS | +| --- | --- | --- |----------------| +| dga_high_sum_probability | Detect domain generation algorithm (DGA) activity in your network data. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | The job configurations and datafeeds can be found [here](https://github.com/elastic/integrations/blob/main/packages/dga/kibana/ml_module/dga-ml.json). @@ -175,14 +175,14 @@ The job configurations and datafeeds can be found [here](https://github.com/elas To download, refer to the [documentation](integration-docs://reference/problemchild/index.md). -| Name | Description | -| --- | --- | -| 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. | -| problem_child_high_sum_by_host | Looks for a set of one or more malicious child processes on a single host. | -| 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. | -| problem_child_rare_process_by_parent | Looks for rare malicious child processes spawned by a parent process. | -| problem_child_high_sum_by_user | Looks for a set of one or more malicious processes, started by the same user. | -| problem_child_high_sum_by_parent | Looks for a set of one or more malicious child processes spawned by the same parent process. | +| Name | Description | Supported Integrations | Supported OS | +| --- | --- | --- |----------------| +| 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. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) | windows| +| problem_child_high_sum_by_host | Looks for a set of one or more malicious child processes on a single host. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) | 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. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) | windows | +| problem_child_rare_process_by_parent | Looks for rare malicious child processes spawned by a parent process. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) |windows | +| problem_child_high_sum_by_user | Looks for a set of one or more malicious processes, started by the same user. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) |windows | +| problem_child_high_sum_by_parent | Looks for a set of one or more malicious child processes spawned by the same parent process. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Windows](https://www.elastic.co/docs/reference/integrations/windows) |windows | The job configurations and datafeeds can be found [here](https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json). @@ -192,15 +192,15 @@ The job configurations and datafeeds can be found [here](https://github.com/elas To download, refer to the [documentation](integration-docs://reference/ded/index.md). -| Name | Description | -| --- | --- | -| ded_high_sent_bytes_destination_geo_country_iso_code | Detects data exfiltration to an unusual geo-location (by country iso code). | -| ded_high_sent_bytes_destination_ip | Detects data exfiltration to an unusual geo-location (by IP address). | -| ded_high_sent_bytes_destination_port | Detects data exfiltration to an unusual destination port. | -| ded_high_sent_bytes_destination_region_name | Detects data exfiltration to an unusual geo-location (by region name). | -| ded_high_bytes_written_to_external_device | Detects data exfiltration activity by identifying high bytes written to an external device. | -| 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. | -| ded_high_bytes_written_to_external_device_airdrop | Detects data exfiltration activity by identifying high bytes written to an external device via Airdrop. | +| Name | Description | Supported Integrations | Supported OS | +| --- | --- | --- |----------------| +| ded_high_sent_bytes_destination_geo_country_iso_code | Detects data exfiltration to an unusual geo-location (by country iso code). | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | +| ded_high_sent_bytes_destination_ip | Detects data exfiltration to an unusual geo-location (by IP address). | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | +| ded_high_sent_bytes_destination_port | Detects data exfiltration to an unusual destination port. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | +| ded_high_sent_bytes_destination_region_name | Detects data exfiltration to an unusual geo-location (by region name). | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint), [Network Packet Capture](https://www.elastic.co/docs/reference/integrations/network_traffic), [Packetbeat](https://www.elastic.co/docs/reference/beats/packetbeat) | windows, linux | +| ded_high_bytes_written_to_external_device | Detects data exfiltration activity by identifying high bytes written to an external device. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint)| 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. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | +| ded_high_bytes_written_to_external_device_airdrop | Detects data exfiltration activity by identifying high bytes written to an external device via Airdrop. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | macOS | The job configurations and datafeeds can be found [here](https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json). @@ -210,18 +210,18 @@ The job configurations and datafeeds can be found [here](https://github.com/elas To download, refer to the [documentation](integration-docs://reference/lmd/index.md). -| Name | Description | -| --- | --- | -| lmd_high_count_remote_file_transfer | Detects unusually high file transfers to a remote host in the network. | -| lmd_high_file_size_remote_file_transfer | Detects unusually high size of files shared with a remote host in the network. | -| lmd_rare_file_extension_remote_transfer | Detects data exfiltration to an unusual destination port. | -| lmd_rare_file_path_remote_transfer | Detects unusual folders and directories on which a file is transferred. | -| lmd_high_mean_rdp_session_duration | Detects unusually high mean of RDP session duration. | -| lmd_high_var_rdp_session_duration | Detects unusually high variance in RDP session duration. | -| lmd_high_sum_rdp_number_of_processes | Detects unusually high number of processes started in a single RDP session. | -| lmd_unusual_time_weekday_rdp_session_start | Detects an RDP session started at an usual time or weekday. | -| 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. | -| 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. | -| lmd_high_mean_rdp_process_args | Detects unusually high number of process arguments in an RDP session. | +| Name | Description | Supported Integrations | Supported OS | +| --- | --- | --- |----------------| +| lmd_high_count_remote_file_transfer | Detects unusually high file transfers to a remote host in the network. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows, linux | +| lmd_high_file_size_remote_file_transfer | Detects unusually high size of files shared with a remote host in the network. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows, linux | +| lmd_rare_file_extension_remote_transfer | Detects data exfiltration to an unusual destination port. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows, linux | +| lmd_rare_file_path_remote_transfer | Detects unusual folders and directories on which a file is transferred. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows, linux | +| lmd_high_mean_rdp_session_duration | Detects unusually high mean of RDP session duration. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | +| lmd_high_var_rdp_session_duration | Detects unusually high variance in RDP session duration. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | +| lmd_high_sum_rdp_number_of_processes | Detects unusually high number of processes started in a single RDP session. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | +| lmd_unusual_time_weekday_rdp_session_start | Detects an RDP session started at an usual time or weekday. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | 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. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | 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. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | +| lmd_high_mean_rdp_process_args | Detects unusually high number of process arguments in an RDP session. | [{{elastic-defend}}](https://www.elastic.co/docs/reference/integrations/endpoint) | windows | The job configurations and datafeeds can be found [here](https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json).