原文地址: https://www.elastic.co/guide/en/elasticsearch/reference/7.7/built-in-roles.html, 原文档版权归 www.elastic.co 所有

Built-in rolesedit

The Elastic Stack security features apply a default role to all users, including anonymous users. The default role enables users to access the authenticate endpoint, change their own passwords, and get information about themselves.

There is also a set of built-in roles you can explicitly assign to users. These roles have a fixed set of privileges and cannot be updated.

apm_system
Grants access necessary for the APM system user to send system-level data (such as monitoring) to Elasticsearch.
apm_user
Grants the privileges required for APM users (such as read and view_index_metadata privileges on the apm-* and .ml-anomalies* indices).
beats_admin
Grants access to the .management-beats index, which contains configuration information for the Beats.
beats_system

Grants access necessary for the Beats system user to send system-level data (such as monitoring) to Elasticsearch.

  • This role should not be assigned to users as the granted permissions may change between releases.
  • This role does not provide access to the beats indices and is not suitable for writing beats output to Elasticsearch.
data_frame_transforms_admin
Grants manage_data_frame_transforms cluster privileges, which enable you to manage transforms. This role also includes all Kibana privileges for the machine learning features. [7.5.0] Deprecated in 7.5.0. Replaced by transform_admin .
data_frame_transforms_user
Grants monitor_data_frame_transforms cluster privileges, which enable you to use transforms. This role also includes all Kibana privileges for the machine learning features. [7.5.0] Deprecated in 7.5.0. Replaced by transform_user .
enrich_user
Grants access to manage all enrich indices (.enrich-*) and all operations on ingest node pipelines.
ingest_admin

Grants access to manage all index templates and all ingest pipeline configurations.

This role does not provide the ability to create indices; those privileges must be defined in a separate role.

kibana_dashboard_only_user
(This role is deprecated, please use Kibana feature privileges instead). Grants read-only access to the Kibana Dashboard in every space in Kibana. This role does not have access to editing tools in Kibana.
kibana_system

Grants access necessary for the Kibana system user to read from and write to the Kibana indices, manage index templates and tokens, and check the availability of the Elasticsearch cluster. This role grants read access to the .monitoring-* indices and read and write access to the .reporting-* indices. For more information, see Configuring Security in Kibana.

This role should not be assigned to users as the granted permissions may change between releases.

kibana_admin
Grants access to all features in Kibana. For more information on Kibana authorization, see Kibana authorization.
kibana_user
(This role is deprecated, please use the kibana_admin role instead.) Grants access to all features in Kibana. For more information on Kibana authorization, see Kibana authorization.
logstash_admin
Grants access to the .logstash* indices for managing configurations.
logstash_system

Grants access necessary for the Logstash system user to send system-level data (such as monitoring) to Elasticsearch. For more information, see Configuring Security in Logstash.

  • This role should not be assigned to users as the granted permissions may change between releases.
  • This role does not provide access to the logstash indices and is not suitable for use within a Logstash pipeline.
machine_learning_admin
Provides all of the privileges of the machine_learning_user role plus the full use of the machine learning APIs. Grants manage_ml cluster privileges, read access to .ml-anomalies*, .ml-notifications*, .ml-state*, .ml-meta* indices and write access to .ml-annotations* indices. Machine learning administrators also need index privileges for source and destination indices and roles that grant access to Kibana. See Machine learning security privileges.
machine_learning_user
Grants the minimum privileges required to view machine learning configuration, status, and work with results. This role grants monitor_ml cluster privileges, read access to the .ml-notifications and .ml-anomalies* indices (which store machine learning results), and write access to .ml-annotations* indices. Machine learning users also need index privileges for source and destination indices and roles that grant access to Kibana. See Machine learning security privileges.
monitoring_user
Grants the minimum privileges required for any user of X-Pack monitoring other than those required to use Kibana. This role grants access to the monitoring indices and grants privileges necessary for reading basic cluster information. This role also includes all Kibana privileges for the Elastic Stack monitoring features. Monitoring users should also be assigned the kibana_admin role, or another role with access to the Kibana instance.
remote_monitoring_agent
Grants the minimum privileges required to write data into the monitoring indices (.monitoring-*). This role also has the privileges necessary to create Metricbeat indices (metricbeat-*) and write data into them.
remote_monitoring_collector
Grants the minimum privileges required to collect monitoring data for the Elastic Stack.
reporting_user
Grants the specific privileges required for users of X-Pack reporting other than those required to use Kibana. This role grants access to the reporting indices; each user has access to only their own reports. Reporting users should also be assigned additional roles that grant access to Kibana as well as read access to the indices that will be used to generate reports.
snapshot_user
Grants the necessary privileges to create snapshots of all the indices and to view their metadata. This role enables users to view the configuration of existing snapshot repositories and snapshot details. It does not grant authority to remove or add repositories or to restore snapshots. It also does not enable to change index settings or to read or update index data.
superuser
Grants full access to the cluster, including all indices and data. A user with the superuser role can also manage users and roles and impersonate any other user in the system. Due to the permissive nature of this role, take extra care when assigning it to a user.
transform_admin
Grants manage_transform cluster privileges, which enable you to manage transforms. This role also includes all Kibana privileges for the machine learning features.
transform_user
Grants monitor_transform cluster privileges, which enable you to use transforms. This role also includes all Kibana privileges for the machine learning features.
transport_client

Grants the privileges required to access the cluster through the Java Transport Client. The Java Transport Client fetches information about the nodes in the cluster using the Node Liveness API and the Cluster State API (when sniffing is enabled). Assign your users this role if they use the Transport Client.

Using the Transport Client effectively means the users are granted access to the cluster state. This means users can view the metadata over all indices, index templates, mappings, node and basically everything about the cluster. However, this role does not grant permission to view the data in all indices.

watcher_admin

Grants read access to the .watches index, read access to the watch history and the triggered watches index and allows to execute all watcher actions.

watcher_user

Grants read access to the .watches index, the get watch action and the watcher stats.