FortiSOAR™ provides you with a number of pre-installed connectors or built-ins, such as the Database connector that you can use within FortiSOAR™ playbooks, as a connector step, and perform automated operations. These connectors are bundled and named based on the type of operations the connectors can perform. For example, the Database connector would contain actions that you can perform with respect to the database like querying the database. It is easy to extend and enhance these connectors.
Apart from the FortiSOAR™ Built-in connectors, Fortinet also provides a number of connectors for popular integrations like SIEMs, such as FortiSIEM, Splunk, etc., and Ticketing systems such as Jira. You can see a list of published connectors on the FortiSOAR Connectors Documentation site.
The process of installing, configuring, and using connectors is defined in the Introduction to connectors chapter in the "Connectors Guide", which is part of the FortiSOAR™ documentation or see the Installing a connector and Configuring a connector articles.
FortiSOAR™ Built-in connectors are upgraded by default with a FortiSOAR™ upgrade. Use the Content Hub to upgrade your connectors to the latest version. For more information on the connector store, see the Introduction to connectors chapter and see the FortiSOAR Built-in connectors article.
Important: Before you upgrade your FortiSOAR™ version, it is highly recommended that you take a backup of your FortiSOAR™ Built-in connector's (SSH, IMAP, Database, etc.) configuration since the configuration of your FortiSOAR™ Built-in connectors might be reset if there are changes to the configuration parameters across versions.
The FortiSOAR ML Engine connector leverages Machine Learning (ML) and acts as your recommendation engine by analyzing and filtering your existing record data using different algorithms to recommend similar records and predict and assign field values in records. It is based on finding similarities of patterns in historical data. The connector performs the following actions:
For more information on the 'Recommendation Engine' and how to configure the FortiSOAR ML Engine connector, see the "Recommendation Engine > Record Similarity and Field Predictions" topic of the Application Editor chapter in the "Administration Guide", which is part of the FortiSOAR™ product documentation.
response_from_primary' tag is set to 'true' in the operations metadata of the info.json file.FortiSOAR™ provides you with a number of pre-installed connectors or built-ins, such as the Database connector that you can use within FortiSOAR™ playbooks, as a connector step, and perform automated operations. These connectors are bundled and named based on the type of operations the connectors can perform. For example, the Database connector would contain actions that you can perform with respect to the database like querying the database. It is easy to extend and enhance these connectors.
Apart from the FortiSOAR™ Built-in connectors, Fortinet also provides a number of connectors for popular integrations like SIEMs, such as FortiSIEM, Splunk, etc., and Ticketing systems such as Jira. You can see a list of published connectors on the FortiSOAR Connectors Documentation site.
The process of installing, configuring, and using connectors is defined in the Introduction to connectors chapter in the "Connectors Guide", which is part of the FortiSOAR™ documentation or see the Installing a connector and Configuring a connector articles.
FortiSOAR™ Built-in connectors are upgraded by default with a FortiSOAR™ upgrade. Use the Content Hub to upgrade your connectors to the latest version. For more information on the connector store, see the Introduction to connectors chapter and see the FortiSOAR Built-in connectors article.
Important: Before you upgrade your FortiSOAR™ version, it is highly recommended that you take a backup of your FortiSOAR™ Built-in connector's (SSH, IMAP, Database, etc.) configuration since the configuration of your FortiSOAR™ Built-in connectors might be reset if there are changes to the configuration parameters across versions.
The FortiSOAR ML Engine connector leverages Machine Learning (ML) and acts as your recommendation engine by analyzing and filtering your existing record data using different algorithms to recommend similar records and predict and assign field values in records. It is based on finding similarities of patterns in historical data. The connector performs the following actions:
For more information on the 'Recommendation Engine' and how to configure the FortiSOAR ML Engine connector, see the "Recommendation Engine > Record Similarity and Field Predictions" topic of the Application Editor chapter in the "Administration Guide", which is part of the FortiSOAR™ product documentation.
response_from_primary' tag is set to 'true' in the operations metadata of the info.json file.