Summary
In this chapter, we looked at how a detection pipeline can be used to automate and enforce your detection team’s processes. We examined the steps of a standard detection engineering pipeline and looked at some more complex examples to see how a pipeline can be modified based on individual use cases.
The Publishing a rule using Elastic’s detection-rules project lab was used to demonstrate how a team can build and leverage a set of capabilities to add structure and process to the creation of their detections. In this example, we performed the steps of our pipeline manually. These steps can be automated using a tool such as Jenkins, or a source repository site such as GitHub or GitLab can manage the pipeline as well.
The detection_rules package was built to support Elastic’s internal detection team. While this package can be used and modified to support your own team’s processes, you should choose the processes that align with your individual...
