Panther Analysis Tool Commands

Use PAT to manage your Panther content

Overview

You can manage your Panther detection content using the Panther Analysis Tool (PAT). PAT lets you upload, test, and delete assets, among other actions.

Each of the PAT commands accepts certain options. For example, you can use --filter with several of the commands to narrow the scope of the action.

PAT commands

See the full list of available PAT commands in the following codeblock. Beneath it, find additional information about several of the commands.

PAT commands can be run using panther_analysis_tool or pat. Learn more about these aliases here.

To understand which Panther permissions you need to execute each PAT command, see Permissions required per command.

$ pat --help
                                                                                                                                       
Usage: pat [OPTIONS] COMMAND [ARGS]...                                                                                                
                                                                                                                                       
Panther Analysis Tool: A command line tool for managing Panther policies and rules.                                                   
                                                                                                                                       
                                                                                                                                       
╭─ Options ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --version                     Show the version and exit                                                                             │
│ --debug                       Enable debug mode                                                                                     │
│ --skip-version-check          Skip Panther version check                                                                            │
│ --install-completion          Install completion for the current shell.                                                             │
│ --show-completion             Show completion for the current shell, to copy it or customize the installation.                      │
│ --help                        Show this message and exit.                                                                           │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ 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.                                             │
│ debug                   Run a single rule test in a debug environment, which allows you to see print statements and use             │
│                         breakpoints.                                                                                                │
│ publish                 Publishes a new release, generates the release assets, and uploads them. Generates a file called            │
│                         panther-analysis-all.zip and optionally generates panther-analysis-all.sig                                  │
│ upload                  Upload specified policies and rules to a Panther deployment.                                                │
│ delete                  Delete policies, rules, or saved queries from a Panther deployment.                                         │
│ update-custom-schemas   Update or create custom schemas on 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.                                     │
│ check-connection        Check your Panther API connection                                                                           │
│ benchmark               Performance test one rule against one of its log types. The rule must be the only item in the working       │
│                         directory or specified by --path, --ignore-files, and --filter. This feature is an extension of Data Replay │
│                         and is subject to the same limitations.                                                                     │
│ enrich-test-data        Enrich test data with additional enrichments from the Panther API.                                          │
│ check-packs             Ensure that packs don't have missing detections.                                                            │
│ init                    Initialize a new panther project                                                                            │
│ update                  Update and merge the latest content from Panther Analysis with your own. Rerun this every time you want to    │
│                         update your content. Items with the same ID as a Panther Analysis Item and a BaseVersion field will be      │
│                         merged with the latest Panther Analysis Item. Items that have merge conflicts will be skipped to be         │
│                         resolved manually with the `merge` command. Use the --write-merge-conflicts flag to write all merge         │
│                         conflicts to their respective files instead of skipping them.                                               │
│ install                 Install and enable an analysis item from Panther Analysis into your local repository.                         │
│ explore                 Explore the latest Panther Analysis content                                                                 │
│ merge                   Merge an analysis item with the latest Panther Analysis content                                      │
│ migrate                 Migrate all analysis items that are based off Panther Analysis content by adding a BaseVersion field and    │
│                         getting them up to date.                                                                                    │
│ fmt                     Format and standardize the code in the current directory to help with making less changes in other          │
│                         commands.                                                                                                   │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

init: Preparing your Panther directory

This command should only be run once, when first setting up your Panther directory.

It:

  • Creates a .gitignore file, if needed, and adds to it

  • Enables git rerere

  • Creates a .cache directory, which locally stores content from panther-analysis for fast loading

    • Pulls the latest content from panther-analysis

migrate: Transitioning content from a legacy management flow

migrate tells PAT to start tracking existing analysis items for future updates.

Running pat migrate looks in your repository, and:

  • For each analysis item with an ID that matches an ID in panther-analysis:

    • Adds a BaseVersion field to the YAML file.

    • Merges your item with the latest version from panther-analysis.

      • If there are merge conflicts, PAT leaves the item un-merged. To resolve the conflict, run pat migrate <ID>.

      • You can optionally use the --auto-accept flag to completely avoid merge conflicts.

        circle-info

        Please note: pat migrate <ID> is for solving merge conflicts while you are still migrating. Items that ran into merge conflicts during pat migrate have not been migrated yet. This is very similar to pat merge <ID>, which is used to solve merge conflicts after running pat update. The merge command should not be used during the migration phase.

  • For each analysis item with an ID that does not match an ID in panther-analysis, no change is made to the item, as it is considered custom.

The output of this command is stored in ./migration_status.md.

update: Fetching and merging the latest panther-analysis content

Rerun this every time you want to update your content.

This command fetches the latest panther-analysis content, and merges it into your own. PAT knows that an item needs updating by determining if an analysis item has the same ID as an item in panther-analysis and if the BaseVersion is less than the latest version of the item in panther-analysis. If an item has the same ID as something in panther-analysis but has no BaseVersion field it will not receive updates. Likewise, if an item does not have a matching ID in panther-analysis but has a BaseVersion field, it will not receive updates.

Items that have merge conflicts will not be updated as a part of pat update, and must be resolved manually with the merge command. A list of all the items that had merge conflicts will be printed out in the output of the update command.

circle-info

If you have merge conflicts arising from pat update, you can resolve them with pat merge (though this is not required to test and upload the content that was successfully updated).

Use the --write-merge-conflicts flag to write all merge conflicts to their respective files instead of skipping them (This may be useful if you're using AI to solve conflicts). Use --auto-accept panthers or --auto-accept yours to automatically resolve merge conflicts (note that the item could still have issues or failing tests even after resolving conflicts, each item should be reviewed after resolving).

Use the --preview flag to do a dry-run of the update. This flag will have the command print the IDs of the items that will be updated and the items that will have merge conflicts without updating any of the files.

explore: Viewing available panther-analysis content

Run pat explore to view the panther-analysis content in your .cache directory. (This command fetches new p-a content if it is out of date with the latest p-a release.) You can search by content ID, type, or description.

You can access the Analysis Content tree using tab. Press enter on any analysis type to filter by it. Press enter on any single analysis ID to filter by it.

The search bar can be used to filter the items in the table. You can search for plain text, which will filter items containing the text in their YAML or python files, case sensitive. You can also search using the filters available in the command line. For example, a search of data "prod env" AnalysisType=rule Severity=Critical,High would do a case sensitive search for any item with data in its YAML or python, prod env in its YAML or python, the analysis type of rule, and a severity of Critical or High. You can use single or double quotes to group words together in the search. All quotes must have their matching end quote to apply the search. Double quotes can be escaped with a backslash (\). Single quotes cannot be escaped.

Pressing enter on a specific item will open its source code. For analysis types that have YAML and Python files, you will be shown both, side-by-side.

circle-info

When viewing a certain item, you can use ^v to install and enable it (rather than using the separate pat install command).

You can exit the explorer GUI with ctrl+q or ctrl+c.

install: Copy and enable a panther-analysis item

Run pat install to copy items from panther-analysis into your own repository. (To understand what you'd like to install, it's recommended to run pat explore.)

If you install an analysis item that has a dependency (like a global helper or data model), the dependency will be installed (replicated in your own repository) as well.

fmt: Format and standardize the code

Run to format and standardize the code in the current directory. There are some formatting changes that are required as part of using PAT. This command lets you easily make formatting changes separately from all other changes the tool makes. Use this to keep logic changes and formatting changes independent of each other while interacting with PAT.

Changes it makes to YAML files are:

  • Normalizes all boolean casing (e.g. True -> true)

  • Standardizes all indentation to 2 spaces

  • Replaces explicit nulls with empty values (e.g. Field: null -> Field: )

  • Replaces all inline style fields with block style, and JSON with block style

  • Removes any newlines within strings without explicit multiline markers (like | and >)

merge: Merge an analysis item with the latest Panther Analysis version of the item

circle-info

pat merge <ID> is for solving merge conflicts after a pat update. If you are still migrating code, use pat migrate <ID> to migrate items with merge conflicts.

After running pat update, you might run into merge conflicts that prevent the analysis item from being cleanly updated. To merge your item with the latest version from Panther Analysis and solve merge conflicts, run pat merge <ID>, with ID being the ID of the analysis item you want to solve merge conflicts for.

YAML merge conflicts will be solved inside a custom YAML merge conflict resolver tool. This will allow you to quickly compare things field by field, choosing your version or Panther's version to resolve the conflict. This tool allows you to avoid merge conflicts that occur from formatting changes, as this tool compares changes field by field instead of line by line. It will only compare top-level fields in your YAML.

After any YAML conflicts, the command will let you solve Python merge conflicts. By default, this will happen inside of vi. You can specify a different editor to use by providing the --editor flag or setting the EDITOR environment variable. The editor must be available as a CLI command to be used. Some editors do not install their CLI commands by default, so please be sure to verify you have your preferred editor available via the CLI.

After successfully solving the merge conflicts, the command will update the BaseVersion field in the YAML for you.

If you prefer to solve merge conflicts differently, you can supply the following flags:

  • --auto-accept: Works the same as it does with other commands. It accepts yours or panthers as values. Will avoid merge conflicts by automatically solving with one side of the merge.

  • --write-merge-conflicts: Writes all the merge conflicts, unresolved, to their files. Doing so will not resolve any conflicts and will not avoid whitespace YAML conflicts. BaseVersion will be updated.

test: Running unit tests

Use PAT to load the defined specification files and evaluate unit tests locally:

To filter rules or policies based on certain attributes:

circle-info

Running pat test for correlation rules and Simple Detections requires an API token. See Authenticating with an API token for more information.

debug: Debug a test using print statements and breakpoints

Use debug to run a specific unit test in debug mode:

See print statements:

See your errors with traceback info:

benchmark: Evaluating rule performance

You can use benchmark to test the performance of an existing or draft rule against one hour of data, for one log type. It can be particularly useful to iterate on a rule that is timing out. This is a long-running command intended to be used manually, as needed—not in a regular CI/CD workflow.

The API token used with this command must be granted the "Read Panther Metrics" (also known as SummaryRead) and "Manage Rules" (also known as RuleModify) permissions. Because benchmark is an extension of Data Replay, it is subject to the same limitations.

You must provide a single rule to benchmark, either by having just one rule in the working directory (./ or --path), or through the use of --ignore-files or --filter.

If you do not specify a certain hour of data, the system will select the historical hour with the highest volume of data. To specify a specific hour to run against, use --hour. (Most common time formats are supported, e.g., 2023-07-31T09:00:00-7:00—minutes, seconds, etc. will be truncated). For example:

For a rule with multiple log types, one must be specified using --log-type. For example:

The output of benchmark will be written to both stdout, and to the directory indicated by the --out option.

enrich-test-data: Enriching test data with Enrichment content

Use enrich-test-data to enrich the test content of your Rules and Scheduled Rules with data from connected Enrichment providers and custom Lookup Tables. This allows you to build more sophisticated test cases for detections that rely on enrichment content.

enrich-test-data is simple to use, but may introduce substantial changes to your analysis YAML files. The command will modify files based on the following criteria:

  • If the Rule or Scheduled Rule does not have test cases, the YAML file will not be modified.

  • If the log type does not support enrichment, the YAML file will not be modified.

  • If the log type supports enrichment and there are test cases:

    • Test cases represented as inline JSON content will be reformatted into YAML.

    • The YAML file will be formatted according to common YAML conventions, using two spaces for indentation.

Similar to other commands, enrich-test-data works from the current directory, recursively. If you run the command at the root directory of your panther-analysis copy, it will attempt to enrich all Rules and Scheduled Rules. To enrich content in a single directory, navigate to that directory before running the command.

You can run enrich-test-data in PAT versions 0.26 and beyond using the following command:

The output of the command will be written to stdout, including a list of any Rules or Scheduled Rules that were enriched.

validate: Ensuring detection content is ready to be uploaded

The validate command verifies your detection content is ready to be uploaded to your Panther instance by running the same checks that happen during the upload process. Because some of these checks require configuration information in your Panther instance, validate makes an API call.

To validate your detections against your Panther instance using PAT:

  1. Run the following command:

    {% code fullWidth="false" %}

    {% endcode %}

    • You may exclude the --api-token and --api-host options if you are setting configuration values another way, i.e., by using environment variables or a configuration file.

zip: Creating a package to upload to the Panther Console

To create a package for uploading manually to the Panther Console, run the following command:

Uploading content in the Panther Console

  1. In the lefthand side of the Panther Console, click Detections.

  2. Click the Upload button in the upper right corner.

  3. Drag and drop your .zip file onto the page, or click Select file.

upload: Uploading packages to Panther directly

circle-info

Starting with PAT version 0.22.0, if you have authenticated with an API token and execute the upload command, an asynchronous bulk upload will automatically be performed, to prevent timeout issues.

If you did not use an API token to authenticate, you can use the --batch option. The --batch option is only available in versions of PAT after 0.19.0.

The upload command uploads your detection content to your Panther instance.

To use upload:

  1. Run panther_analysis_tool test to ensure your unit tests are passing.

  2. Run the following command: panther_analysis_tool upload --path <path-to-your-detections> --api-token <your-api-token> --api-host https://api.<your-panther-instance-name>.runpanther.net/public/graphql

    • You may exclude the --api-token and --api-host options if you are setting configuration values another way, i.e., by using environment variables or a configuration file.

When using upload, detections and Lookup Tables with existing IDs are overwritten. Locally deleted detections will not automatically be deleted in your Panther instance on upload—they must be removed with the delete command (or manually deleted in your Panther Console). When using the CLI workflow, it's recommended to set a detection's Enabled property to false, instead of deleting.

If you update the ID of an entity (i.e., the value of RuleId or PolicyId) and use upload—but do not also use delete to manually remove the old entity, both versions will exist in your Panther instance. If you intend to update the ID without creating a duplicate detection, use delete with the old ID.

The CreatedBy detection field

By default, detections uploaded in the CLI workflow (i.e., with PAT or via the REST API) are shown on the Detections list page in the Panther Console as created by Panther:

A table with headers and one row is shown. A header/row value pair (Created By / Panther) is circled.

If you'd like to customize the Created By value for a detection uploaded in the CLI workflow, you can add a CreatedBy key to your detection's YAML file. The value of CreatedBy can be:

  • A Panther user's email address: in the Console, the Created By field will show the associated user.

  • A Panther user's unique ID: in the Console, the Created By field will show the associated user.

  • An arbitrary text value: in the Panther Console, the provided value will be displayed with (External) appended to it.

    A table with headers and four row values is shown. A "Created By" column with the values in the first three rows is circled.

The CreatedBy key can be used in definitions for Python rules, scheduled rules, correlation rules, simple detections, and policies.

If you download a detection from the Panther Console:

  • If it was created in the Panther Console, it will not contain CreatedBy.

  • If it was uploaded in the CLI workflow:

    • With CreatedBy, it will contain CreatedBy.

    • Without CreatedBy, it will not contain CreatedBy.

delete: Deleting Rules, Policies, or Saved Queries

While panther_analysis_tool upload --path <directory> will upload everything from <directory>, it will not delete anything in your Panther instance if you simply remove a local file from <directory>. Instead, you can use the panther_analysis_tool delete command to explicitly delete detections from your Panther instance. To delete a specific detection, you can run the following command:

This will interactively ask you for a confirmation before it deletes the detection. If you would like to delete without confirming, you can use the following command:

You can delete up to 1000 detections at once with PAT.

update-custom-schemas: Creating or updating custom schemas

Use update-custom-schemas to create or update custom schemas.

circle-exclamation

Permissions required per command

Below is a mapping of permissions required for each command.

Command
Required permission(s)

check-connection

Read Panther Settings Info

test (when testing detections that use Inline Filtersarrow-up-right)

Bulk Upload OR Bulk Upload Validate OR View Rules

benchmark

Read Panther Metrics

validate

Bulk Upload Validate OR Bulk Upload

upload

Bulk Upload

delete

Manage Policies Manage Rules Manage Saved Searches

update-custom-schemas

View Log Sources Manage Log Sources

PAT command options

Each PAT command has options (also known as flags), which you can view by running $ pat <command> -h.

chevron-rightExample output of pat test -hhashtag

If an option takes multiple arguments, you must pass each value individually with the option. For example, to pass two arguments to --valid-table-names:

  • Correct: --valid-table-names table1 --valid-table-names table2

  • Incorrect: --valid-table-names table1 table2

If a multi-argument option accepts values in the format KEY=VALUE1,VALUE2 (like --filter), each one must be passed to the flag separately (though the argument's value can still be represented as a comma-separated array). For example:

  • Correct: --filter AnalysisType=policy,rule --filter Severity=High

  • Incorrect: --filter AnalysisType=policy,rule Severity=High

--filter: Filtering PAT commands

The test, zip, upload, and release commands all support filtering. Filtering works by passing the --filter flag 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 analysis types 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:

The following command will test items with the AnalysisType policy OR rule, AND the Severity High:

When writing policies or rules that refer to the global analysis type, 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:

For this query to work as expected, we need to allow for the severity field to be absent:

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

--minimum-tests: Requiring a certain number of unit tests

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. 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.

In the example below, even though each of the rule tests passed, they're still considered failing because they do not have the correct test coverage:

Last updated

Was this helpful?