Snowflake Integration

Panther can be configured to write processed log data to one or more AWS-based Snowflake database clusters. This allows you to join Panther processed data with your other data sources in Snowflake.

Integrating Panther with Snowflake enables Panther data to be used in your Business Intelligence tools to make dashboards tailored to you operations. In addition, you can join Panther data (e.g., Panther alerts) to your business data, enabling assessment of your security posture with respect to your organization.

For example, you can tally alerts by organizational division (e.g., Human Resources) or by infrastructure (e.g., Development, Test, Production).

Panther uses Snowpipe to copy the data into your Snowflake cluster.

Configuration Overview

There are three parts to configuring Panther to integrate with Snowflake.

Part 1: Configure the Panther user interface with an AWS Secret for access

Part 2: Configure Panther to ingest data into Snowflake

Part 3: Update permissions and test Panther user interface with Snowflake

Configure the Panther User Interface with an AWS Secret for access

Create a user associated with a read-only role in your Snowflake account.

Create a secret in the AWS Secrets Manager. Ideally this should be created in the same AWS region as the Panther deployment but this is optional. This secret will be used by Panther to read database tables. It will be configured to only allow access from a single lambda function in the Panther account.

First, create a KMS key to use for an secret. Go to the KMS console and click on Create a key. Pick Symmetric for the type and click Next. On the next screen set the alias to panther-secret. Click Next. On the next page Click Next (accept defaults). On the next page click on Add another AWS Account and enter the account id where Panther is installed. Click Next. Click Finish.

Now, access the AWS Secrets Manager via the console and select Store a New Secret button on the page.

Second, you will be presented with a page titled Store a new secret. Select Other type of secrets from the list of types. Specify the following key/value pairs:

  • account (NOTE: this can be found by clicking on the snowflake console on your login name)

  • user

  • password

  • host (NOTE: this is usually:

  • port (NOTE: use 443 unless you have configured differently)

Select panther-secret from the dropdown under Select the encryption key.

Then click Next.


You will be presented with a screen asking for the name and description of the secret. Fill these in and click Next.


The next screen concerns autorotation, just click the Next button.


Finally you will be presented with an overview screen. Scroll to the bottom and click the Store button.

If using a pre-packaged deployment then update the SecretsManagerARN attribute with the ARN of the secret in the CloudFormation template inputs or in the panther_config.yml file if deploying from source.

# Setting this configures SnowflakeAPI allowing the Data Explorer and scheduled queries to
# access data in Snowflake. This is the ARN of a secret in AWS Secrets Manager with the following attributes:
# * account
# * user
# * password
# * host
# * port
# For example:
# SecretsManagerARN: arn:aws:secretsmanager:us-east-2:05060362XXXX:secret:panther-snowflake-secret-x1CT28
SecretsManagerARN: arn:aws:secretsmanager:eu-central-1:18532453XXXX:secret:panther-snowflake-secret-Uk9bBw

Configure Data Ingest into Snowflake

In order to configure Panther, you need to get the SNOWFLAKE_IAM_USER from Snowflake.

In a Snowflake SQL shell execute the below sql, replacing myaccountid with your AWS account ID and myaccountregion with the account's region:

SELECT system$get_aws_sns_iam_policy('arn:aws:sns:myaccountregion:myaccountid:panther-processed-data-notifications');

You should see a response of:


In the above example, the SNOWFLAKE_IAM_USER is the AWS attribute arn:aws:iam::34318291XXXX:user/k7m2-s-v2st0722.

Edit your deployments/panther_config.yml to add arn:aws:iam::34318291XXXX:user/k7m2-s-v2st0722 the to Snowflake configuration:

# Snowflake ( Integration
# List of Snowflake cluster IAM ARNs which will ingest the output of Panther log processing.
# If this list is non-empty, a file will be produced by `mage snowflake:snowpipe`
# called './out/snowflake/showpipe.sql' that should be run in your snowflake cluster
# to configure Snowpipe and declare the Panther tables.
# For example:
# DestinationClusterARNs:
# - arn:aws:iam::34318291XXXX:user/k8m1-s-v2st0721 # test snowflake cluster
# - arn:aws:iam::34318291XXXX:user/h1h4-s-a2st0111 # production snowflake cluster
- arn:aws:iam::34318291XXXX:user/k7m2-s-v2st0722

If deploying using a pre-packaged deployment also update DestinationClusterARNs as above in the CloudFormation inputs.

Next, run mage deploy if deploying from source or deploy via the pre-packaged deployment using CloudFormation.

When the deployment is done, run mage snowflake:snowpipe. When finished there should be a snowpipe.sql file created in ./out/snowflake/snowpipe.sql

In the Snowflake SQL shell use the Load Script option to load snowpipe.sql


Select the All Queries checkbox, then click on Run


Validation of Snowpipe Processing

Once snowpipe.sql has been successfully executed, you should have three databases:

  • panther_logs

  • panther_rule_matches

  • panther_views

These are the same database names used in AWS Athena and queries should behave similarly.

Assuming you have data being regularly being processed, there should be data in the tables in a few minutes.

You can quickly test if the data ingestion is working by running simple queries, for example:

SELECT count(1) AS c FROM panther_logs.public.aws_cloudtrail ;

Update Permissions and Test Panther User Interface with Snowflake

Update the Panther Snowflake user with grants to read tables from the following databases:

  • panther_logs

  • panther_rule_matches

  • panther_views

You may want to allow more tables so that you can join data to the Panther data from the Panther Data Explorer.

We need to configure the permissions for the Panther AWS secret. Go to the console and select the secret you created above. On the overview screen click on the Edit Permissions button. Copy the below policy JSON, substituting the <snowflake api lambda role> at the top of the generated ./out/snowflake/snowpipe.sql file from above, and <secret ARN> for the ARN of the secret just created.

"Version": "2012-10-17",
"Statement": [
"Effect": "Allow",
"Principal": {"AWS": "<snowflake api lambda role>" },
"Action": "secretsmanager:GetSecretValue",
"Resource": "<secret ARN>"

Then click the Save button.

The configuration can be tested from the Data Explorer. Run some same queries over a table that you know has data (check via Snowflake console).

To rotate secrets, create a NEW read-only user and edit the secret replacing the old user and password with the new user and password. Wait one hour before deleting/disabling the the old user in Snowflake.