generate.py

#!/usr/bin/python

'''
Generates splunk configurations from manifest files under the security_content repo.
'''

import glob
import yaml
import argparse
from os import path
import sys
import datetime
from jinja2 import Environment, FileSystemLoader
import re
from attackcti import attack_client
import csv


def load_objects(file_path, VERBOSE, REPO_PATH):
    files = []
    manifest_files = path.join(path.expanduser(REPO_PATH), file_path)
    for file in sorted(glob.glob(manifest_files)):
        if VERBOSE:
            print("processing manifest: {0}".format(file))
        files.append(load_file(file))
    return files


def load_file(file_path):
    with open(file_path, 'r', encoding="utf-8") as stream:
        try:
            file = list(yaml.safe_load_all(stream))[0]
        except yaml.YAMLError as exc:
            print(exc)
            sys.exit("ERROR: reading {0}".format(file_path))
    return file


def generate_transforms_conf(lookups, TEMPLATE_PATH, OUTPUT_PATH):
    sorted_lookups = sorted(lookups, key=lambda i: i['name'])

    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('transforms.j2')
    output_path = path.join(OUTPUT_PATH, 'default/transforms.conf')
    output = template.render(lookups=sorted_lookups, time=utc_time)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return output_path

def generate_collections_conf(lookups, TEMPLATE_PATH, OUTPUT_PATH):
    filtered_lookups = list(filter(lambda i: 'collection' in i, lookups))
    sorted_lookups = sorted(filtered_lookups, key=lambda i: i['name'])

    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('collections.j2')
    output_path = path.join(OUTPUT_PATH, 'default/collections.conf')
    output = template.render(lookups=sorted_lookups, time=utc_time)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return output_path

def generate_savedsearches_conf(detections, response_tasks, baselines, deployments, TEMPLATE_PATH, OUTPUT_PATH):
    '''
    @param detections: input list of individual YAML detections in detections/ directory
    @param response_tasks:
    @param baselines:
    @param deployments:
    @return: the savedsearches.conf file located in package/default/
    '''

    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    j2_env.filters['custom_jinja2_enrichment_filter'] = custom_jinja2_enrichment_filter
    template = j2_env.get_template('savedsearches.j2')
    output_path = path.join(OUTPUT_PATH, 'default/savedsearches.conf')
    output = template.render(detections=detections, baselines=baselines, response_tasks=response_tasks, time=utc_time)
    with open(output_path, 'w') as f:
        output = output.encode('ascii', 'ignore').decode('ascii')
        f.write(output)

    return output_path

def generate_analytic_story_conf(stories, detections, response_tasks, baselines, TEMPLATE_PATH, OUTPUT_PATH):
    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('analytic_stories.j2')
    output_path = path.join(OUTPUT_PATH, 'default/analytic_stories.conf')
    output = template.render(stories=stories, time=utc_time)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return output_path

def generate_use_case_library_conf(stories, detections, response_tasks, baselines, TEMPLATE_PATH, OUTPUT_PATH):
    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('use_case_library.j2')
    output_path = path.join(OUTPUT_PATH, 'default/use_case_library.conf')
    output = template.render(stories=stories, detections=detections,
                             response_tasks=response_tasks,
                             baselines=baselines, time=utc_time)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return output_path

def generate_macros_conf(macros, detections, TEMPLATE_PATH, OUTPUT_PATH):
    filter_macros = []
    for detection in detections:
        new_dict = {}
        new_dict['definition'] = 'search *'
        new_dict['description'] = 'Update this macro to limit the output results to filter out false positives. '
        new_dict['name'] = detection['name']. \
            replace(' ', '_').replace('-', '_').replace('.', '_').replace('/', '_').lower() + '_filter'
        filter_macros.append(new_dict)

    all_macros = macros + filter_macros

    utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat()

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('macros.j2')
    output_path = path.join(OUTPUT_PATH, 'default/macros.conf')
    output = template.render(macros=all_macros, time=utc_time)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return output_path

def generate_workbench_panels(response_tasks, stories, TEMPLATE_PATH, OUTPUT_PATH):
    workbench_panel_objects = []
    for response_task in response_tasks:
        if 'search' in response_task:
            if 'inputs' in response_task:
                response_file_name = response_task['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower()
                response_file_name_xml = response_file_name + "___response_task.xml"
                response_task['lowercase_name'] = response_file_name
                workbench_panel_objects.append(response_task)
                j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                                     trim_blocks=True)
                template = j2_env.get_template('panel.j2')
                file_path = "default/data/ui/panels/workbench_panel_" + response_file_name_xml
                output_path = path.join(OUTPUT_PATH, file_path)
                response_task['search']= response_task['search'].replace(">",">")
                response_task['search']= response_task['search'].replace("<","&lt;")

                output = template.render(search=response_task['search'])
                with open(output_path, 'w') as f:
                    f.write(output)

    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('es_investigations.j2')
    output_path = path.join(OUTPUT_PATH, 'default/es_investigations.conf')
    output = template.render(response_tasks=workbench_panel_objects, stories=stories)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)
    j2_env = Environment(loader=FileSystemLoader(TEMPLATE_PATH),
                         trim_blocks=True)
    template = j2_env.get_template('workflow_actions.j2')
    output_path = path.join(OUTPUT_PATH, 'default/workflow_actions.conf')
    output = template.render(response_tasks=workbench_panel_objects)
    with open(output_path, 'w', encoding="utf-8") as f:
        f.write(output)

    return workbench_panel_objects


def parse_data_models_from_search(search):
    match = re.search(r'from\sdatamodel\s?=\s?([^\s.]*)', search)
    if match is not None:
        return match.group(1)
    return False

def parse_author_company(story):
    match_author = re.search(r'^([^,]+)', story['author'])
    if match_author is None:
        match_author = 'no'
    else:
        match_author = match_author.group(1)

    match_company = re.search(r',\s?(.*)$', story['author'])
    if match_company is None:
        match_company = 'no'
    else:
        match_company = match_company.group(1)

    return match_author, match_company


def get_deployments(object, deployments):
    matched_deployments = []

    for deployment in deployments:

        for tag in object['tags'].keys():
            if tag in deployment['tags'].keys():
                if type(object['tags'][tag]) is str:
                    tag_array = [object['tags'][tag]]
                else:
                    tag_array = object['tags'][tag]

                for tag_value in tag_array:
                    if type(deployment['tags'][tag]) is str:
                        tag_array_deployment = [deployment['tags'][tag]]
                    else:
                        tag_array_deployment = deployment['tags'][tag]

                    for tag_value_deployment in tag_array_deployment:
                        if tag_value == tag_value_deployment:
                            # print("tag value: {}, matched deployment tag: {} on deployment: {}".format(tag_value,tag_value_deployment, deployment))
                            matched_deployments.append(deployment)
                            continue

    # grab default for all stories if deployment not set
    if len(matched_deployments) == 0:
        for deployment in deployments:
            if 'analytic_story' in deployment['tags']:
                if deployment['tags']['analytic_story'] == 'all':
                    last_deployment = deployment
    else:
        last_deployment = matched_deployments[-1]
        # last_deployment = replace_vars_in_deployment(last_deployment, object) # Not needed because of custom_jinja2_enrichment_filter

    # print(last_deployment)
    return last_deployment

def get_nes_fields(search, deployment):
    nes_fields_matches = []
    if 'alert_action' in deployment:
        if 'notable' in deployment['alert_action']:
            if 'nes_fields' in deployment['alert_action']['notable']:
                for field in deployment['alert_action']['notable']['nes_fields']:
                    if (search.find(field + ' ') != -1):
                        nes_fields_matches.append(field)

    return nes_fields_matches


def map_response_tasks_to_stories(response_tasks):
    sto_res = {}
    for response_task in response_tasks:
        if 'tags' in response_task:
            if 'analytic_story' in response_task['tags']:
                for story in response_task['tags']['analytic_story']:
                    if 'type' in response_task.keys():
                        if response_task['type'] == 'response':
                            task_name = str('ESCU - ' + response_task['name'] + ' - Response Task')
                    else:
                        task_name = str('ESCU - ' + response_task['name'] + ' - Response Task')
                    if not (story in sto_res):
                        sto_res[story] = {task_name}
                    else:
                        sto_res[story].add(task_name)
    return sto_res

def map_baselines_to_stories(baselines):
    sto_bas = {}
    for baseline in baselines:
        if 'tags' in baseline:
            if 'analytic_story' in baseline['tags']:
                for story in baseline['tags']['analytic_story']:
                    if 'type' in baseline.keys():
                        if baseline['type'] == 'batch':
                            baseline_name = str('ESCU - ' + baseline['name'])
                    else:
                        baseline_name = str('ESCU - ' + baseline['name'])
                    if not (story in sto_bas):
                        sto_bas[story] = {baseline_name}
                    else:
                        sto_bas[story].add(baseline_name)
    return sto_bas

def custom_jinja2_enrichment_filter(string, object):
    customized_string = string
    for key in object.keys():
        [key.encode('utf-8') for key in object]
        customized_string = customized_string.replace("%" + key + "%", str(object[key]))

    for key in object['tags'].keys():
        customized_string = customized_string.replace("%" + key + "%", str(object['tags'][key]))

    return customized_string


def prepare_detections(detections, deployments, OUTPUT_PATH):
    for detection in detections:
        # parse out data_models
        data_model = parse_data_models_from_search(detection['search'])
        if data_model:
            detection['data_model'] = data_model

        matched_deployment = get_deployments(detection, deployments)
        detection['deployment'] = matched_deployment
        nes_fields = get_nes_fields(detection['search'], detection['deployment'])
        if len(nes_fields) > 0:
            detection['nes_fields'] = nes_fields

        keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist']
        mappings = {}
        for key in keys:
            if key == 'mitre_attack':
                if 'mitre_attack_id' in detection['tags']:
                    mappings[key] = detection['tags']['mitre_attack_id']
            else:
                if key in detection['tags']:
                    mappings[key] = detection['tags'][key]
        detection['mappings'] = mappings

        # used for upstream processing of risk scoring annotations in ECSU
        # this is not currently compatible with newer instances of ESCU (6.3.0+)
        # we are duplicating the code block above for now and just changing variable names to make future
        # changes to this data structure separate from the mappings generation
        # @todo expose the JSON data structure for newer risk type
        annotation_keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist', 'analytic_story']
        savedsearch_annotations = {}
        for key in annotation_keys:
            if key == 'mitre_attack':
                if 'mitre_attack_id' in detection['tags']:
                    savedsearch_annotations[key] = detection['tags']['mitre_attack_id']
            else:
                if key in detection['tags']:
                    savedsearch_annotations[key] = detection['tags'][key]
        detection['savedsearch_annotations'] = savedsearch_annotations

        if 'risk_object' in detection['tags']:
            detection['risk_object'] = detection['tags']['risk_object']
        if 'risk_object_type' in detection['tags']:
            detection['risk_object_type'] = detection['tags']['risk_object_type']
        if 'risk_score' in detection['tags']:
            detection['risk_score'] = detection['tags']['risk_score']
        if 'product' in detection['tags']:
            detection['product'] = detection['tags']['product']
        if (OUTPUT_PATH) == 'dist/saaws':
            detection['disabled'] = 'false'

    return detections

def prepare_baselines(baselines, deployments, OUTPUT_PATH):
    for baseline in baselines:
        data_model = parse_data_models_from_search(baseline['search'])
        if data_model:
            baseline['data_model'] = data_model
        if (OUTPUT_PATH) == 'dist/saaws':
            baseline['disabled'] = 'false'

        matched_deployment = get_deployments(baseline, deployments)
        baseline['deployment'] = matched_deployment

    return baselines

def prepare_response_tasks(response_tasks):
    for response_task in response_tasks:
        if 'search' in response_task:
            data_model = parse_data_models_from_search(response_task['search'])
            if data_model:
                response_task['data_model'] = data_model

    return response_tasks

def prepare_stories(stories, detections, response_tasks, baselines):
    # enrich stories with information from detections: data_models, mitre_ids, kill_chain_phases, nists
    sto_to_data_models = {}
    sto_to_mitre_attack_ids = {}
    sto_to_kill_chain_phases = {}
    sto_to_ciss = {}
    sto_to_nists = {}
    sto_to_det = {}
    for detection in detections:
        if 'analytic_story' in detection['tags']:
            for story in detection['tags']['analytic_story']:
                if 'type' in detection.keys():
                    if detection['type'] == 'batch':
                        rule_name = str('ESCU - ' + detection['name'] + ' - Rule')
                else:
                    rule_name = str('ESCU - ' + detection['name'] + ' - Rule')

                if story in sto_to_det.keys():
                    sto_to_det[story].add(rule_name)
                else:
                    sto_to_det[story] = {rule_name}

                data_model = parse_data_models_from_search(detection['search'])
                if data_model:
                    if story in sto_to_data_models.keys():
                        sto_to_data_models[story].add(data_model)
                    else:
                        sto_to_data_models[story] = {data_model}

                if 'mitre_attack_id' in detection['tags']:
                    if story in sto_to_mitre_attack_ids.keys():
                        for mitre_attack_id in detection['tags']['mitre_attack_id']:
                            sto_to_mitre_attack_ids[story].add(mitre_attack_id)
                    else:
                        sto_to_mitre_attack_ids[story] = set(detection['tags']['mitre_attack_id'])

                if 'kill_chain_phases' in detection['tags']:
                    if story in sto_to_kill_chain_phases.keys():
                        for kill_chain in detection['tags']['kill_chain_phases']:
                            sto_to_kill_chain_phases[story].add(kill_chain)
                    else:
                        sto_to_kill_chain_phases[story] = set(detection['tags']['kill_chain_phases'])

                if 'cis20' in detection['tags']:
                    if story in sto_to_ciss.keys():
                        for cis in detection['tags']['cis20']:
                            sto_to_ciss[story].add(cis)
                    else:
                        sto_to_ciss[story] = set(detection['tags']['cis20'])

                if 'nist' in detection['tags']:
                    if story in sto_to_nists.keys():
                        for nist in detection['tags']['nist']:
                            sto_to_nists[story].add(nist)
                    else:
                        sto_to_nists[story] = set(detection['tags']['nist'])

    sto_res = map_response_tasks_to_stories(response_tasks)
    sto_bas = map_baselines_to_stories(baselines)

    for story in stories:
        story['author_name'], story['author_company'] = parse_author_company(story)
        story['lowercase_name'] = story['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower()
        story['detections'] = sorted(sto_to_det[story['name']])
        story['searches'] = story['detections']
        if story['name'] in sto_to_data_models:
            story['data_models'] = sorted(sto_to_data_models[story['name']])
        if story['name'] in sto_to_mitre_attack_ids:
            story['mitre_attack'] = sorted(sto_to_mitre_attack_ids[story['name']])
        if story['name'] in sto_to_kill_chain_phases:
            story['kill_chain_phases'] = sorted(sto_to_kill_chain_phases[story['name']])
        if story['name'] in sto_to_ciss:
            story['cis20'] = sorted(sto_to_ciss[story['name']])
        if story['name'] in sto_to_nists:
            story['nist'] = sorted(sto_to_nists[story['name']])
        if story['name'] in sto_res:
            story['response_tasks'] = sorted(list(sto_res[story['name']]))
            story['searches'] = story['searches'] + story['response_tasks']
            story['workbench_panels'] = []
            for response_task_name in story['response_tasks']:
                s = 'panel://workbench_panel_' + response_task_name[7:].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower()
                story['workbench_panels'].append(s)
        if story['name'] in sto_bas:
            story['baselines'] = sorted(list(sto_bas[story['name']]))


        keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist']
        mappings = {}
        for key in keys:
            if key in story:
                mappings[key] = story[key]

        story['mappings'] = mappings

    return stories


def generate_mitre_lookup(OUTPUT_PATH):

    csv_mitre_rows = [["mitre_id", "technique", "tactics", "groups"]]

    lift = attack_client()
    all_enterprise = lift.get_enterprise(stix_format=False)
    enterprise_relationships = lift.get_enterprise_relationships()
    enterprise_groups = lift.get_enterprise_groups()

    for technique in all_enterprise['techniques']:
        apt_groups = []
        for relationship in enterprise_relationships:
            if (relationship['target_ref'] == technique['id']) and relationship['source_ref'].startswith('intrusion-set'):
                for group in enterprise_groups:
                    if relationship['source_ref'] == group['id']:
                        apt_groups.append(group['name'])

        if not ('revoked' in technique):
            if len(apt_groups) == 0:
                apt_groups.append('no')
            csv_mitre_rows.append([technique['technique_id'], technique['technique'], '|'.join(technique['tactic']).replace('-',' ').title(), '|'.join(apt_groups)])

    with open(path.join(OUTPUT_PATH, 'lookups/mitre_enrichment.csv'), 'w', newline='', encoding="utf-8") as file:
        writer = csv.writer(file)
        writer.writerows(csv_mitre_rows)


def import_objects(VERBOSE, REPO_PATH):
    objects = {
        "stories": load_objects("stories/*.yml", VERBOSE, REPO_PATH),
        "macros": load_objects("macros/*.yml", VERBOSE, REPO_PATH),
        "lookups": load_objects("lookups/*.yml", VERBOSE, REPO_PATH),
        "baselines": load_objects("baselines/*.yml", VERBOSE, REPO_PATH),
        "responses": load_objects("responses/*.yml", VERBOSE, REPO_PATH),
        "response_tasks": load_objects("response_tasks/*.yml", VERBOSE, REPO_PATH),
        "deployments": load_objects("deployments/*.yml", VERBOSE, REPO_PATH),
        "detections": load_objects("detections/*/*.yml", VERBOSE, REPO_PATH),
    }
    objects["detections"].extend(load_objects("detections/*/*/*.yml", VERBOSE, REPO_PATH))

    return objects

def compute_objects(objects, PRODUCT, OUTPUT_PATH):
    if PRODUCT == "SAAWS":
        objects["detections"]  = [object for object in objects["detections"]  if 'Splunk Security Analytics for AWS' in object['tags']['product']]
        objects["stories"] = [object for object in objects["stories"] if 'Splunk Security Analytics for AWS' in object['tags']['product']]
        objects["baselines"] = [object for object in objects["baselines"] if 'Splunk Security Analytics for AWS' in object['tags']['product']]
        objects["response_tasks"] = [object for object in objects["response_tasks"] if 'Splunk Security Analytics for AWS' in object['tags']['product']]

    # only use ESCU detections to the configurations
    objects["detections"] = sorted(filter(lambda d: d['type'].lower() == 'batch', objects["detections"]), key=lambda d: d['name'])
    # only use ESCU stories to the configuration
    objects["stories"] = sorted(filter(lambda s: s['type'].lower() == 'batch', objects["stories"]), key=lambda s: s['name'])

    objects["response_tasks"] = sorted(objects["response_tasks"], key=lambda i: i['name'])
    objects["baselines"] = sorted(objects["baselines"], key=lambda b: b['name'])
    objects["macros"] = sorted(objects["macros"], key=lambda m: m['name'])

    objects["detections"] = prepare_detections(objects["detections"], objects["deployments"], OUTPUT_PATH)
    objects["baselines"] = prepare_baselines(objects["baselines"], objects["deployments"], OUTPUT_PATH)
    objects["response_tasks"] = prepare_response_tasks(objects["response_tasks"])
    objects["stories"] = prepare_stories(objects["stories"], objects["detections"], objects["response_tasks"], objects["baselines"])

    return objects

def get_objects(REPO_PATH, OUTPUT_PATH, PRODUCT, VERBOSE):
    objects = import_objects(VERBOSE, REPO_PATH)
    objects = compute_objects(objects, PRODUCT, OUTPUT_PATH)
    return objects

def main(REPO_PATH, OUTPUT_PATH, PRODUCT, VERBOSE):

    TEMPLATE_PATH = path.join(REPO_PATH, 'bin/jinja2_templates')

    objects = get_objects(REPO_PATH, OUTPUT_PATH, PRODUCT, VERBOSE)

    try:
        if VERBOSE:
            print("generating Mitre lookups")
        generate_mitre_lookup(OUTPUT_PATH)
    except Exception as e:
        print('Error: ' + str(e))
        print("WARNING: Generation of Mitre lookup failed.")

    lookups_path = generate_transforms_conf(objects["lookups"], TEMPLATE_PATH, OUTPUT_PATH)
    lookups_path = generate_collections_conf(objects["lookups"], TEMPLATE_PATH, OUTPUT_PATH)

    detection_path = generate_savedsearches_conf(objects["detections"], objects["response_tasks"], objects["baselines"], objects["deployments"], TEMPLATE_PATH, OUTPUT_PATH)

    story_path = generate_analytic_story_conf(objects["stories"], objects["detections"], objects["response_tasks"], objects["baselines"], TEMPLATE_PATH, OUTPUT_PATH)

    use_case_lib_path = generate_use_case_library_conf(objects["stories"], objects["detections"], objects["response_tasks"], objects["baselines"], TEMPLATE_PATH, OUTPUT_PATH)

    macros_path = generate_macros_conf(objects["macros"], objects["detections"], TEMPLATE_PATH, OUTPUT_PATH)

    workbench_panels_objects = generate_workbench_panels(objects["response_tasks"], objects["stories"], TEMPLATE_PATH, OUTPUT_PATH)


    if VERBOSE:
        print("{0} stories have been successfully written to {1}".format(len(objects["stories"]), story_path))
        print("{0} detections have been successfully written to {1}".format(len(objects["detections"]), detection_path))
        print("{0} response tasks have been successfully written to {1}".format(len(objects["response_tasks"]), detection_path))
        print("{0} baselines have been successfully written to {1}".format(len(objects["baselines"]), detection_path))
        print("{0} macros have been successfully written to {1}".format(len(objects["macros"]), macros_path))
        print("{0} workbench panels have been successfully written to {1}, {2} and {3}".format(len(workbench_panels_objects), OUTPUT_PATH + "/default/es_investigations.conf", OUTPUT_PATH + "/default/workflow_actions.conf", OUTPUT_PATH + "/default/data/ui/panels/*"))
        print("security content generation completed..")


if __name__ == "__main__":

    parser = argparse.ArgumentParser(description="generates splunk conf files out of security_content manifests", epilog="""
    This tool converts manifests to the source files to be used by products like Splunk Enterprise.
    It generates the savesearches.conf, analytics_stories.conf files for ES.""")
    parser.add_argument("-p", "--path", required=True, help="path to security_content repo")
    parser.add_argument("-o", "--output", required=True, help="path to the output directory")
    parser.add_argument("-v", "--verbose", required=False, default=False, action='store_true', help="prints verbose output")
    parser.add_argument("--product", required=True, default="ESCU", help="package type")

    # parse them
    args = parser.parse_args()
    REPO_PATH = args.path
    OUTPUT_PATH = args.output
    VERBOSE = args.verbose
    PRODUCT = args.product

    main(REPO_PATH, OUTPUT_PATH, PRODUCT, VERBOSE)