Panther Developer Workflows Overview
Panther Developer Workflows are non-Panther Console workflows you can use to interact with your Panther account
Last updated
Panther Developer Workflows are non-Panther Console workflows you can use to interact with your Panther account
Last updated
Panther Developer Workflows are non-Panther Console workflows you can use to interact with your Panther account, including , , the , the , and other operational tools.
This page describes the developer workflows and tools you can use with Panther. Panther Developer Workflows are intended for a technical audience who feels comfortable using non-Console workflows.
Looking for information on using web application-based workflows?
To learn more about getting started in the Panther Console, check out the .
For information on managing detections in the Panther Console, see the .
Automate your detection pipeline and improve security with a CI/CD workflow: Leverage the Panther-managed Python detections from the panther-analysis repository in GitHub, adapt the detections to fit into your CI/CD pipeline, and upload the detections to your Panther Console.
For general information and best practices for Panther detections, see the .
CI/CD users can make use of Panther-managed detections written in Python in the . This can be done by maintaining a public fork of the repo or maintaining a cloned private repository.
The detections in panther-analysis are broadly applicable, but can be customized to ensure that you are receiving only the alerts that are most important to your organization. You will need to pull updates from panther-analysis to take advantage of new detections.
For instructions, see .
Panther offers CI/CD documentation specific to using the following platforms:
Note that you can adapt these instructions to fit other workflows.
Your uploaded detections will appear alongside detections that were created manually in the Panther Console.
Panther does not support using both a CLI workflow and a manual workflow in the Panther Console simultaneously to create and manage detections.
The Panther API supports operations for token rotation, alerting, cloud account management, log source management, user and role management, data lake queries, and user metrics.
Panther itself uses an extended version of the API internally, so any changes you make using the Panther API will be immediately reflected in the Panther Console.
Common use cases include:
Managing your users through IaaC and automating Role creation
Getting the latest Panther metrics to use in your own dashboards
Resolving an alert in Panther as part of an external workflow
Running a custom Data Explorer query whenever a certain event occurs
Panther provides two developer tools that you can use within your workflows:
Panther Analysis Tool (PAT): An open-source utility for testing, packaging, and deploying Panther detections from source code.
Pantherlog: A CLI tool that you can use to infer and parse logs, validate schema files, and run unit tests.
is an open-source utility for testing, packaging, and deploying Panther detections from source code. It's designed for developer-centric workflows such as managing your Panther detections programmatically or within CI/CD pipelines.
Panther offers a public GraphQL-over-HTTP API, meaning you can write GraphQL queries and invoke the API using a typical HTTP request. For more information on GraphQL, please see. The Panther API can integrate with any existing tools that you have. Whether via scripts or CI/CD workflows, the API gives you the ability to automate workflows and complete tasks quickly by codifying processes that would normally require a manual login to the Panther Console.
For full documentation, as well as end-to-end examples in Python and NodeJS, please see .
You can manage parts of your Panther log source infrastructure using . Terraform allows you to define and provision your infrastructure through code, making it easy to manage and track changes across your project's lifecycle. in the Terraform registry.
See a full example of using Terraform to manage an S3 log source on .
For instructions on using PAT, see the .
For instructions on using pantherlog, see the .