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Panther command line interface for writing, testing, and packaging policies/rules.

Project description

Panther Analysis Tool

Command Line Panther Analysis Management

Documentation | Quick Start


panther_analysis_tool is a Python CLI for testing, packaging, and deploying Panther Detections defined in code. See the Panther documentation for more details on Panther.

Installation

Install simply with pip:

pip3 install panther_analysis_tool

If you would rather use the panther_analysis_tool outside of the virtual environment, install it directly:

make deps
pip3 install -e .

Build From Source

If you'd prefer instead to run from source for development reasons, first setup your environment:

make install
pipenv run -- pip3 install -e .

Commands and Usage

View available commands:

$ panther_analysis_tool -h


usage: panther_analysis_tool [-h] [--version] [--debug] {release,test,upload,delete,test-lookup-table,zip} ...

Panther Analysis Tool: A command line tool for managing Panther policies and rules.

positional arguments:
  {release,test,upload,delete,test-lookup-table,zip}
    release             Create release assets for repository containing panther detections. Generates a file called panther-analysis-all.zip and optionally generates panther-analysis-all.sig
    test                Validate analysis specifications and run policy and rule tests.
    upload              Upload specified policies and rules to a Panther deployment.
    delete              Delete policies, rules, or saved queries from a Panther deployment
    test-lookup-table   Validate a Lookup Table spec file.
    validate            Validate your bulk uploads against your panther instance
    zip                 Create an archive of local policies and rules for uploading to Panther.

optional arguments:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --debug

Run tests:

$ panther_analysis_tool test --path tests/fixtures/valid_policies/
[INFO]: Testing analysis packs in tests/fixtures/valid_policies/

AWS.IAM.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

Upload Packages

Create packages to upload via the Panther UI:

$ panther_analysis_tool zip --path tests/fixtures/valid_policies/ --out tmp
[INFO]: Testing analysis packs in tests/fixtures/valid_policies/

AWS.IAM.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

[INFO]: Zipping analysis packs in tests/fixtures/valid_policies/ to tmp
[INFO]: <current working directory>/tmp/panther-analysis-2020-03-23T12-48-18.zip

Upload packages to Panther directly.

Note, this expects your environment to be setup the same way as if you were using the AWS CLI, see the setup instructions here. We also recommend using a credentials manager such as aws-vault.

$ panther_analysis_tool upload --path tests/fixtures/valid_policies/ --out tmp
[INFO]: Testing analysis packs in tests/fixtures/valid_policies/

AWS.IAM.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

AWS.IAM.BetaTest
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

AWS.CloudTrail.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

[INFO]: Zipping analysis packs in tests/fixtures/valid_policies/ to tmp
[INFO]: Found credentials in environment variables.
[INFO]: Uploading pack to Panther
[INFO]: Upload success.
[INFO]: API Response:
{
  "modifiedPolicies": 0,
  "modifiedRules": 0,
  "newPolicies": 2,
  "newRules": 1,
  "totalPolicies": 2,
  "totalRules": 1
}

Filtering

The test, zip, and upload commands all support filtering. Filtering works by passing the --filter argument with a list of filters specified in the format KEY=VALUE1,VALUE2. The keys can be any valid field in a policy or rule. When using a filter, only anaylsis that matches each filter specified will be considered. For example, the following command will test only items with the AnalysisType of policy AND the severity of High:

panther_analysis_tool test --path tests/fixtures/valid_policies --filter AnalysisType=policy Severity=High
[INFO]: Testing analysis packs in tests/fixtures/valid_policies

AWS.IAM.BetaTest
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

Whereas the following command will test items with the AnalysisType policy OR rule, AND the severity High:

panther_analysis_tool test --path tests/fixtures/valid_policies --filter AnalysisType=policy,rule Severity=High
[INFO]: Testing analysis packs in tests/fixtures/valid_policies

AWS.IAM.BetaTest
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

AWS.CloudTrail.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

When writing policies or rules that refer to the global analysis types, be sure to include them in your filter. You can include an empty string as a value in a filter, and it will mean the filter is only applied if the field exists. The following command will return an error, because the policy in question imports a global but the global does not have a severity so it is excluded by the filter:

panther_analysis_tool test --path tests/fixtures/valid_policies --filter AnalysisType=policy,global Severity=Critical
[INFO]: Testing analysis packs in tests/fixtures/valid_policies

AWS.IAM.MFAEnabled
	[ERROR] Error loading module, skipping

Invalid: tests/fixtures/valid_policies/example_policy.yml
	No module named 'panther'

[ERROR]: [('tests/fixtures/valid_policies/example_policy.yml', ModuleNotFoundError("No module named 'panther'"))]

If you want this query to work, you need to allow for the severity field to be absent like this:

panther_analysis_tool test --path tests/fixtures/valid_policies --filter AnalysisType=policy,global Severity=Critical,""
[INFO]: Testing analysis packs in tests/fixtures/valid_policies

AWS.IAM.MFAEnabled
	[PASS] Root MFA not enabled fails compliance
	[PASS] User MFA not enabled fails compliance

Filters work for the zip and upload commands in the exact same way they work for the test command.

In addition to filtering, you can set a minimum number of unit tests with the --minimum-tests flag. Detections that don't have the minimum number of tests will be considered failing, and if --minimum-tests is set to 2 or greater it will also enforce that at least one test must return True and one must return False.

panther_analysis_tool test --path tests/fixtures/valid_policies --minimum-tests 2
% panther_analysis_tool test --path okta_rules --minimum-tests 2
[INFO]: Testing analysis packs in okta_rules

Okta.AdminRoleAssigned
	[PASS] Admin Access Assigned

Okta.BruteForceLogins
	[PASS] Failed login

Okta.GeographicallyImprobableAccess
	[PASS] Non Login
	[PASS] Failed Login

--------------------------
Panther CLI Test Summary
	Path: okta_rules
	Passed: 0
	Failed: 3
	Invalid: 0

--------------------------
Failed Tests Summary
	Okta.AdminRoleAssigned
		['Insufficient test coverage, 2 tests required but only 1 found.', 'Insufficient test coverage: expected at least one passing and one failing test.']

	Okta.BruteForceLogins
		['Insufficient test coverage, 2 tests required but only 1 found.', 'Insufficient test coverage: expected at least one passing and one failing test.']

	Okta.GeographicallyImprobableAccess
		['Insufficient test coverage: expected at least one passing and one failing test.']

So in this case even though the rules passed all their tests, they're still considered failing because they do not have the correct test coverage.

Delete Rules, Policies, or Saved Queries from a Panther deployment.

Like the Upload commands mentioned above, this option requires your environment to be configured as if you are using AWS-CLI

optional arguments:
  -h, --help            show this help message and exit
  --no-confirm          Skip manual confirmation of deletion
  --athena-datalake     Instance DataLake is backed by Athena
  --aws-profile AWS_PROFILE
                        The AWS profile to use when updating the AWS Panther deployment.
  --analysis-id ANALYSIS_ID [ANALYSIS_ID ...]
                        Space separated list of Rule or Policy IDs
  --query-id QUERY_ID [QUERY_ID ...]
                        Space separated list of Saved Queries

You must pass a space separated list of Analysis IDs (RuleID or PolicyID) or QueryIDs. Use the --no-confirm flag to bypass a confirmation prompt. Rules will be matched with any associated saved queries and vice versa, and both associated items will be deleted. By default, this option is configured to talk to a Snowflake datalake, if your Panther instance is backed by an Athena datalake pass the flag --athena-datalake.

Configuration File

Panther Analysis Tool will also read options from a configuration file called .panther_settings.yml located in your working directory. An example configuration file is included in this repo, example_panther_config.yml, that contains example syntax for supported options.

Note that options in the configuration file override options passed on the command line. For example if you set minimum_tests: 2 in the configuration file and --minimum-tests 1 on the command line the minimum number of tests will be 2.

Contributing

We welcome all contributions! Please read the contributing guidelines before submitting pull requests. Instructions for opening a pull request from your fork of the repo can be found on Github.

Local Development

To work on the panther_analysis_tool locally you will need two repos ready: this one and a repo with your panther analysis content to test PAT on.

From your panther analysis content repo run

pipenv install --editable ../relative/path/to/panther_analysis_tool

Then you can test your changes to PAT by running

pipenv run panther_analysis_tool <cmd>

License

This repository is licensed under the AGPL-3.0 license.

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