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Powered by GitBook
On this page
  • Step 1: Contact Panther’s Tech Partner team
  • Step 2: Determine the integration method(s)
  • Step 3: Generate schema(s)
  • Verifying your data is flowing into Panther
  • Step 4: Write instructional information about the integration
  • Step 5: Submit to Panther for review
  • Step 6 (Optional): Create detections for your log source

Was this helpful?

  1. Data Sources & Transports

Tech Partner Log Source Integrations

Integrate your product with Panther as a Tech Partner

PreviousTarsal Onboarding GuideNextDetections

Last updated 7 months ago

Was this helpful?

This page provides instructions for who are integrating their product with Panther by sending logs to one of Panther's —for example, to an or an . If you need to create a log pulling integration instead, please work directly with the Panther Tech Partner team.

If you would instead like to create an Alert Destination integration, see . If you are a Panther customer looking for information on ingesting custom logs, please see the .

Step 1: Contact Panther’s Tech Partner team

  • to contact our Tech Partner team.

    • You will work with our Tech Partner team to get access to an NFR (Not for Resale) Panther instance and a shared Slack channel.

Step 2: Determine the integration method(s)

  • If your application can export events to an S3 bucket, please see the .

  • If your data can use one of our other transport options, please see the individual pages.

The is not recommended if your log source is high-volume (i.e., it emits at least one GB per hour) and/or its .

Step 3: Generate schema(s)

  1. Generate one or more schemas for your data:

    1. Generate sample data.

    2. Determine how many log schemas you will need to create—see on Custom Logs.

    3. Infer your schema(s) using your sample data.

      • You can or .

      • If you are inferring more than one schema, it's recommended to use either the method or the method.

    4. Review the inferred schema(s) for the following:

      • If you generated more than one schema and they have a common set of required properties, events may be misclassified, as the event classification process decides which schema an incoming event belongs to based on the required properties of the schema. If your schemas have the same required properties and you can't differentiate them, consider merging the schemas.

      • If a timestamp property can be used to define the time the event occurred, mark it with isEventTime: true , otherwise its p_parse_time will be used as its event time, and that may lead to inaccurate event timestamps.

      • Consider any that may help make the events easier to reference or manipulate in detections or searches.

    5. Export your schema(s).

      • You can export your schema(s) , or you can copy them from the Panther Console and paste it into a text file.

Verifying your data is flowing into Panther

  1. In the left-hand navigation bar of your Panther Console, click Investigate > Search.

  2. Click Search.

    • Look for events in the results table at the bottom of the page.

Step 4: Write instructional information about the integration

Please create a text file with the following information, which will be used to describe your platform in the Panther Console and to generate a documentation page for this integration:

  • A description of the application

  • Common use cases

  • The supported integration method(s)

  • Any caveats or limitations

  • Step-by-step instructions on how to make any necessary configurations in your application to forward logs from your service to the Data Transport source

    • If these instructions are outlined on your public documentation, feel free to share a link to that instead

Step 5: Submit to Panther for review

  1. Zip the files containing the following:

    • The text file of information from Step 4

    • A square .svg file of the application’s logo

    • Your test data

    • The schema

  2. Send the zipped file to Panther via your shared Slack channel.

After submitting your zip file, the Tech Partner team will work with you to coordinate next steps.

Step 6 (Optional): Create detections for your log source

    • This is strongly encouraged, as having detections available will promote adoption of your integration.

At this stage—before a log source tile for your organization has been added in Panther—you may wish to test your integration by setting up a source. After you have configured the source, you can verify that data is being ingested into Panther by using the tool.

You can learn more about Search on , but on a high level:

In the in the upper-right corner, click the name(s) of your log source's schema(s).

Adjust the , if needed.

For an example, see pages under that use Data Transports, such as and

Write Python for your log source.

See to learn how to get started, and find full examples in the .

Open a Pull Request with your detection content against the .

Please follow the and .

Data Transport
Search
its documentation page
Supported Logs
Auth0 Logs
GitLab Logs
detections
Writing Python Detections
panther-analysis GitHub repository
public panther-analysis GitHub repository
contribution guidelines
style guide
Panther Technology Partners
Data Transport sources
S3 bucket
HTTP endpoint
Tech Partner Alert Destination Integrations
Custom Logs documentation
Fill out this form
S3 Source instructions
Data Transport documentation
HTTP source
transformations
payload size exceeds the HTTP payload limit
from the CLI using pantherlog
from the CLI using pantherlog
Determine how many custom schemas you need
infer a schema in the Panther Console
Inferring a custom schema from sample logs
Inferring custom schemas from historical S3 data
table dropdown filter
date/time range filter