Badger Maps and Iris Dfir integration

Make sure you have n8n installed and running:

• Install n8n on any platform using npm or Docker;
• Or let n8n host it for you on its cloud infrastructure.

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow.

Add the starting point – a trigger on when your workflow should run: on an app event, on schedule, on a webhook call, when called by another workflow, or manually. In some cases, the HTTP Request node might already serve as your starting point.

Add the HTTP Request node to your workflow canvas and authenticate it using a predefined credential type. This allows you to perform custom operations, without additional authentication setup.

Click on the HTTP node to configure its settings. Use the Iris Dfir API docs to construct your request. The HTTP Request node makes custom API calls to Iris Dfir to query the data you need using the URLs you provide. See the example here.

Add the HTTP Request node to your workflow canvas and authenticate it using a generic authentication method. The HTTP Request nodes make custom API calls to Iris Dfir to query the data you need using the URLs you provide. See the example here.

Click on the HTTP node to configure its settings. With generic authentication, you'll typically need to provide endpoint URLs, headers, parameters, and any other authentication details specific to the service you're integrating with:

• Find the documentation of the Badger Maps API and see if the API supports HTTP requests;
• Most APIs require some form of authentication and you can configure this in the HTTP Request mode (Basic Auth, Custom Auth, Digest Auth, Header Auth, OAuth1 API, OAuth2 API, Query Auth).

Connect the output of the Iris Dfir node to the input of the Badger Maps node or swop nodes to route the integration the other way around.

Use n8n's core nodes to transform data the way you need and extend the integration:

• Splitting: IF and Switch
• Merging: Merge, Compare Datasets
• Looping: IF and Loop Over Items
• Waiting: Wait
• Creating sub-workflows: Execute Workflow and Execute Workflow Trigger
• Error handling: Stop And Error and Error Trigger
• Code: write custom JavaScript or Python and run it as a step in your workflow.

Once you've configured everything, make sure to save your workflow and activate it. Activating a workflow means that it will run automatically every time a trigger node receives input or meets a condition. By default, all newly created workflows are deactivated.

Run the workflow to see if everything is working as expected. Based on your configuration, data should flow from Badger Maps to Iris Dfir or vice versa. Easily debug your workflow: you can check past executions to isolate the mistake and fix it.