technique_mapping.py

import simplejson
import xlsxwriter
from datetime import datetime
from generic import *
from file_output import *
from navigator_layer import *
from copy import deepcopy
# Imports for pandas and plotly are because of performance reasons in the function that uses these libraries.


def _set_platform(platform_yaml, platform_args, domain):
    """
    Get the correct value for the ATT&CK platform(s). Use the platform(s) from the YAML file or the ones provided via the CLI arguments.
    :param platform_yaml: the platform(s) key-value pair from the YAML file
    :param platform_args: the platform list as provided by the user
    :param domain: the specified domain
    :return: platform(s) in a list
    """
    if isinstance(platform_args, list):
        if 'all' in platform_args:
            selected_platforms = PLATFORMS_ENTERPRISE if domain == 'enterprise-attack' else PLATFORMS_ICS if domain == 'ics-attack' else PLATFORMS_MOBILE
            platform = list(selected_platforms.values())
        else:
            platform = platform_args
    else:
        platform = platform_yaml

    return platform


def _write_layer(layer, mapped_techniques, filename_prefix, name, output_filename):
    """
    Writes the json layer file to disk.
    :param layer: the prepped layer dictionary
    :param mapped_techniques: the techniques section that will be included in the layer
    :param filename_prefix: the prefix for the output filename
    :param name: the name that will be used in the filename together with the prefix
    :param output_filename: the output filename defined by the user
    :return:
    """
    layer['techniques'] = mapped_techniques
    json_string = simplejson.dumps(layer).replace('}, ', '},\n')
    if not output_filename:
        output_filename = create_output_filename(filename_prefix, name)
    else:
        if output_filename.endswith('.json'):
            output_filename = output_filename.replace('.json', '')
        if filename_prefix == 'visibility_and_detection':
            output_filename += '_overlay'
    write_file(output_filename, json_string)


def _map_and_colorize_techniques_for_detections(my_techniques, domain, count_detections, layer_settings):
    """
    Determine the color of the techniques based on the detection score in the given YAML file. Also, it will create
    much of the content for the Navigator layer.
    :param my_techniques: the configured techniques
    :param domain: the specified domain
    :param count_detections: option for the Navigator layer output: count detections instead of listing detections
    :param layer_settings: settings for the Navigator layer
    :return: a dictionary with techniques that can be used in the layer's output file
    """
    techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH_ENTERPRISE if domain ==
                                  'enterprise-attack' else DATA_TYPE_STIX_ALL_TECH_ICS if domain == 'ics-attack' else DATA_TYPE_STIX_ALL_TECH_MOBILE)

    # Color the techniques based on how the coverage defined in the detections definition and generate a list with
    # techniques to be used in the layer output file.
    mapped_techniques = []
    technique_id = ""
    try:
        for technique_id, technique_data in my_techniques.items():
            technique = get_technique(techniques, technique_id)
            s = calculate_score(technique_data['detection'], zero_value=-1)
            
            tactics = []
            if 'includeTactic' in layer_settings.keys() and layer_settings['includeTactic'] == 'True':
                for kill_chain_phase in technique['kill_chain_phases']:
                    if kill_chain_phase['kill_chain_name'] == 'mitre-attack':
                        tactics.append(kill_chain_phase['phase_name'])
            else:
                tactics.append(None)

            if s != -1:
                color = COLOR_D_0 if s == 0 else COLOR_D_1 if s == 1 else COLOR_D_2 if s == 2 else COLOR_D_3 \
                    if s == 3 else COLOR_D_4 if s == 4 else COLOR_D_5 if s == 5 else ''

                if technique is not None:
                    x = dict()
                    x['techniqueID'] = technique_id
                    x['color'] = color
                    x['comment'] = ''
                    x['enabled'] = True
                    x['metadata'] = []
                    x['score'] = s

                    if 'showMetadata' not in layer_settings.keys() or ('showMetadata' in layer_settings.keys() and str(layer_settings['showMetadata']) == 'True'):
                        cnt = 1
                        tcnt = len([d for d in technique_data['detection'] if get_latest_score(d) >= 0])
                        for detection in technique_data['detection']:
                            d_score = get_latest_score(detection)
                            if d_score >= 0:
                                location = ''
                                if count_detections:
                                    location_count = count_detections_in_location(detection['location'])

                                    for l, c in location_count.items():
                                        location += f"{l}: {c}. "
                                else:
                                    location = ', '.join(detection['location'])

                                applicable_to = ', '.join(detection['applicable_to'])
                                x['metadata'].append({'name': 'Applicable to', 'value': applicable_to})
                                x['metadata'].append({'name': 'Detection score', 'value': str(d_score)})
                                x['metadata'].append({'name': 'Detection location', 'value': location})
                                x['metadata'].append({'name': 'Technique comment', 'value': detection['comment']})
                                x['metadata'].append({'name': 'Detection comment', 'value': get_latest_comment(detection)})
                                if cnt != tcnt:
                                    x['metadata'].append({'divider': True})
                                cnt += 1
                        x['metadata'] = make_layer_metadata_compliant(x['metadata'])
                    
                    for tactic in tactics:
                        if tactic is not None:
                            x['tactic'] = tactic
                        mapped_techniques.append(deepcopy(x))
                else:
                    print('[!] Technique ' + technique_id + ' is unknown in ATT&CK. Ignoring this technique.')
    except Exception as e:
        print('[!] Possible error in YAML file at: %s. Error: %s' % (technique_id, str(e)))
        quit()

    determine_and_set_show_sub_techniques(mapped_techniques, techniques, layer_settings)

    return mapped_techniques


def _map_and_colorize_techniques_for_visibility(my_techniques, platforms, domain, layer_settings):
    """
    Determine the color of the techniques based on the visibility score in the given YAML file.
    :param my_techniques: the configured techniques
    :param platforms: the configured platform(s)
    :param domain: the specified domain
    :param layer_settings: settings for the Navigator layer
    :return: a dictionary with techniques that can be used in the layer's output file
    """
    techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH_ENTERPRISE if domain ==
                                  'enterprise-attack' else DATA_TYPE_STIX_ALL_TECH_ICS if domain == 'ics-attack' else DATA_TYPE_STIX_ALL_TECH_MOBILE)
    applicable_data_sources = get_applicable_data_sources_platform(platforms, domain)
    applicable_dettect_data_sources = get_applicable_dettect_data_sources_platform(platforms, domain)

    # Color the techniques based on how the coverage defined in the detections definition and generate a list with
    # techniques to be used in the layer output file.
    mapped_techniques = []
    for technique_id, technique_data in my_techniques.items():
        s = calculate_score(technique_data['visibility'])
        if s == 0:
            s = None

        technique = get_technique(techniques, technique_id)
        color = COLOR_V_1 if s == 1 else COLOR_V_2 if s == 2 else COLOR_V_3 if s == 3 else COLOR_V_4 if s == 4 else ''
        
        tactics = []
        if 'includeTactic' in layer_settings.keys() and layer_settings['includeTactic'] == 'True':
            for kill_chain_phase in technique['kill_chain_phases']:
                if kill_chain_phase['kill_chain_name'] == 'mitre-attack':
                    tactics.append(kill_chain_phase['phase_name'])
        else:
            tactics.append(None)

        if technique is not None:
            x = dict()
            x['techniqueID'] = technique_id
            x['color'] = color
            x['comment'] = ''
            x['enabled'] = True
            x['metadata'] = []

            if 'showMetadata' not in layer_settings.keys() or ('showMetadata' in layer_settings.keys() and str(layer_settings['showMetadata']) == 'True'):
                x['metadata'].append({'name': 'ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(technique.get('data_components', ''),
                                                                                                                              applicable_data_sources))})
                x['metadata'].append({'name': 'DeTT&CT data sources', 'value': ', '.join(get_applicable_dettect_data_sources_technique(technique['dettect_data_sources'],
                                                                                                                                       applicable_dettect_data_sources))})
                x['metadata'].append({'divider': True})
                x['score'] = s

                cnt = 1
                tcnt = len(technique_data['visibility'])
                for visibility in technique_data['visibility']:
                    applicable_to = ', '.join(visibility['applicable_to'])
                    x['metadata'].append({'name': 'Applicable to', 'value': applicable_to})
                    x['metadata'].append({'name': 'Visibility score', 'value': str(get_latest_score(visibility))})
                    x['metadata'].append({'name': 'Technique comment', 'value': visibility['comment']})
                    x['metadata'].append({'name': 'Visibility comment', 'value': get_latest_comment(visibility)})
                    if cnt != tcnt:
                        x['metadata'].append({'divider': True})
                    cnt += 1
                x['metadata'] = make_layer_metadata_compliant(x['metadata'])

            for tactic in tactics:
                if tactic is not None:
                    x['tactic'] = tactic
                mapped_techniques.append(deepcopy(x))
        else:
            print('[!] Technique ' + technique_id + ' is unknown in ATT&CK. Ignoring this technique.')

    determine_and_set_show_sub_techniques(mapped_techniques, techniques, layer_settings)

    # add metadata with ATT&CK data sources for the ones without visibility:
    for t in techniques:
        tech_id = get_attack_id(t)
        if tech_id not in my_techniques.keys():
            # look if technique already exists in the layer dict (as a result of determine_and_set_show_sub_techniques):
            x = None
            exists = False
            for mapped_tech in mapped_techniques:
                if mapped_tech['techniqueID'] == tech_id:
                    x = mapped_tech
                    exists = True
                    break
            if x is None:
                x = dict()
            
            technique = get_technique(techniques, technique_id)
            tactics = []
            if 'includeTactic' in layer_settings.keys() and layer_settings['includeTactic'] == 'True':
                for kill_chain_phase in technique['kill_chain_phases']:
                    if kill_chain_phase['kill_chain_name'] == 'mitre-attack':
                        tactics.append(kill_chain_phase['phase_name'])
            else:
                tactics.append(None)
            
            x['techniqueID'] = tech_id
            x['comment'] = ''
            x['enabled'] = True

            if 'showMetadata' not in layer_settings.keys() or ('showMetadata' in layer_settings.keys() and str(layer_settings['showMetadata']) == 'True'):
                x['metadata'] = [{'name': 'ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(t['data_components'],
                                                                                                                          applicable_data_sources))}]
                x['metadata'].append({'name': 'DeTT&CT data sources', 'value': ', '.join(get_applicable_dettect_data_sources_technique(t['dettect_data_sources'],
                                                                                                                                       applicable_dettect_data_sources))})
                x['metadata'] = make_layer_metadata_compliant(x['metadata'])

            if not exists:
                for tactic in tactics:
                    if tactic is not None:
                        x['tactic'] = tactic
                    mapped_techniques.append(deepcopy(x))

    return mapped_techniques


def _map_and_colorize_techniques_for_overlaid(my_techniques, platforms, domain, count_detections, layer_settings):
    """
    Determine the color of the techniques based on both detection and visibility.
    :param my_techniques: the configured techniques
    :param platforms: the configured platform(s)
    :param domain: the specified domain
    :param count_detections: option for the Navigator layer output: count detections instead of listing detections
    :param layer_settings: settings for the Navigator layer
    :return: a dictionary with techniques that can be used in the layer's output file
    """
    techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH_ENTERPRISE if domain ==
                                  'enterprise-attack' else DATA_TYPE_STIX_ALL_TECH_ICS if domain == 'ics-attack' else DATA_TYPE_STIX_ALL_TECH_MOBILE)
    applicable_data_sources = get_applicable_data_sources_platform(platforms, domain)
    applicable_dettect_data_sources = get_applicable_dettect_data_sources_platform(platforms, domain)

    # Color the techniques based on how the coverage defined in the detections definition and generate a list with
    # techniques to be used in the layer output file.
    mapped_techniques = []
    for technique_id, technique_data in my_techniques.items():
        detection_score = calculate_score(technique_data['detection'], zero_value=-1)
        visibility_score = calculate_score(technique_data['visibility'])

        detection = True if detection_score > 0 else False
        visibility = True if visibility_score > 0 else False

        if detection and visibility:
            color = COLOR_OVERLAY_BOTH
        elif detection and not visibility:
            s = detection_score
            color = COLOR_D_0 if s == 0 else COLOR_D_1 if s == 1 else COLOR_D_2 if s == 2 else COLOR_D_3 if s == 3 else COLOR_D_4 if s == 4 else COLOR_D_5 if s == 5 else ''
        elif not detection and visibility:
            s = visibility_score
            color = COLOR_V_1 if s == 1 else COLOR_V_2 if s == 2 else COLOR_V_3 if s == 3 else COLOR_V_4 if s == 4 else ''
        elif detection_score == 0:  # forensics/context
            color = COLOR_D_0
        else:
            color = COLOR_WHITE

        technique = get_technique(techniques, technique_id)
        
        tactics = []
        if 'includeTactic' in layer_settings.keys() and layer_settings['includeTactic'] == 'True':
            for kill_chain_phase in technique['kill_chain_phases']:
                if kill_chain_phase['kill_chain_name'] == 'mitre-attack':
                    tactics.append(kill_chain_phase['phase_name'])
        else:
            tactics.append(None)
        
        x = dict()
        x['techniqueID'] = technique_id
        x['color'] = color
        x['comment'] = ''
        x['enabled'] = True
        x['metadata'] = []

        if 'showMetadata' not in layer_settings.keys() or ('showMetadata' in layer_settings.keys() and str(layer_settings['showMetadata']) == 'True'):
            x['metadata'].append({'name': 'ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(technique.get('data_components', ''),
                                                                                                                          applicable_data_sources))})
            x['metadata'].append({'name': 'DeTT&CT data sources', 'value': ', '.join(get_applicable_dettect_data_sources_technique(technique['dettect_data_sources'],
                                                                                                                                   applicable_dettect_data_sources))})
            # Metadata for detection and visibility:
            for obj_type in ['detection', 'visibility']:
                tcnt = len([obj for obj in technique_data[obj_type] if get_latest_score(obj) >= 0])
                if tcnt > 0:
                    x['metadata'] = add_metadata_technique_object(technique_data, obj_type, x['metadata'], count_detections)

            x['metadata'] = make_layer_metadata_compliant(x['metadata'])

        for tactic in tactics:
            if tactic is not None:
                x['tactic'] = tactic
            mapped_techniques.append(deepcopy(x))

    determine_and_set_show_sub_techniques(mapped_techniques, techniques, layer_settings)

    return mapped_techniques


def generate_detection_layer(filename_techniques, overlay, output_filename, layer_name, layer_settings, platform, count_detections):
    """
    Generates layer for detection coverage and optionally an overlaid version with visibility coverage.
    :param filename_techniques: the filename of the YAML file containing the techniques administration
    :param overlay: boolean value to specify if an overlay between detection and visibility should be generated
    :param layer_name: the name of the Navigator layer
    :param output_filename: the output filename defined by the user
    :param layer_settings: settings for the Navigator layer
    :param platform: one or multiple values from PLATFORMS constant
    :param count_detections: option for the Navigator layer output: count detections instead of listing detections
    :return:
    """
    my_techniques, name, platform_yaml, domain = load_techniques(filename_techniques)
    platform = _set_platform(platform_yaml, platform, domain)

    if not overlay:
        mapped_techniques_detection = _map_and_colorize_techniques_for_detections(my_techniques, domain, count_detections, layer_settings)
        if not layer_name:
            layer_name = 'Detections ' + name
        layer_detection = get_layer_template_detections(layer_name, 'description', platform, domain, layer_settings)
        _write_layer(layer_detection, mapped_techniques_detection, 'detection', name, output_filename)
    else:
        mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, platform, domain, count_detections, layer_settings)
        if not layer_name:
            layer_name = 'Visibility and Detection ' + name
        layer_both = get_layer_template_layered(layer_name, 'description', platform, domain, layer_settings)
        _write_layer(layer_both, mapped_techniques_both, 'visibility_and_detection', name, output_filename)


def generate_visibility_layer(filename_techniques, overlay, output_filename, layer_name, layer_settings, platform, count_detections):
    """
    Generates layer for visibility coverage and optionally an overlaid version with detection coverage.
    :param filename_techniques: the filename of the YAML file containing the techniques administration
    :param overlay: boolean value to specify if an overlay between detection and visibility should be generated
    :param output_filename: the output filename defined by the user
    :param layer_name: the name of the Navigator layer
    :param layer_settings: settings for the Navigator layer
    :param platform: one or multiple values from PLATFORMS constant
    :param count_detections: option for the Navigator layer output: count detections instead of listing detections
    :return:
    """
    my_techniques, name, platform_yaml, domain = load_techniques(filename_techniques)
    platform = _set_platform(platform_yaml, platform, domain)

    if not overlay:
        mapped_techniques_visibility = _map_and_colorize_techniques_for_visibility(my_techniques, platform, domain, layer_settings)
        if not layer_name:
            layer_name = 'Visibility ' + name
        layer_visibility = get_layer_template_visibility(layer_name, 'description', platform, domain, layer_settings)
        _write_layer(layer_visibility, mapped_techniques_visibility, 'visibility', name, output_filename)
    else:
        mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, platform, domain, count_detections, layer_settings)
        if not layer_name:
            layer_name = 'Visibility and Detection ' + name
        layer_both = get_layer_template_layered(layer_name, 'description', platform, domain, layer_settings)
        _write_layer(layer_both, mapped_techniques_both, 'visibility_and_detection', name, output_filename)


def plot_graph(filename, type_graph, output_filename):
    """
    Generates a line graph which shows the improvements on detections or visibility through time.
    :param filename: the filename of the YAML file containing the techniques administration
    :param type_graph: indicates the type of the graph: detection or visibility
    :param output_filename: the output filename defined by the user
    :return:
    """
    my_techniques, name, _, _ = load_techniques(filename)

    graph_values = []
    for t in my_techniques.values():
        for item in t[type_graph]:
            date = get_latest_date(item)
            score = get_latest_score(item)
            if date and score > 0:
                yyyymmdd = date.strftime('%Y-%m-%d')
                graph_values.append({'date': yyyymmdd, 'count': 1})

    import pandas as pd
    df = pd.DataFrame(graph_values).groupby('date', as_index=False)[['count']].sum()
    df['cumcount'] = df['count'].cumsum()

    if not output_filename:
        output_filename = 'graph_' + type_graph
    elif output_filename.endswith('.html'):
        output_filename = output_filename.replace('.html', '')
    output_filename = get_non_existing_filename('output/' + output_filename, 'html')

    import plotly
    import plotly.graph_objs as go
    plotly.offline.plot(
        {'data': [go.Scatter(x=df['date'], y=df['cumcount'])],
         'layout': go.Layout(title="# of %s items for %s" % (type_graph, name))},
        filename=output_filename, auto_open=False
    )
    print("File written:   " + output_filename)


def export_techniques_list_to_excel(filename, output_filename):
    """
    Makes an overview of the MITRE ATT&CK techniques from the YAML administration file.
    :param filename: the filename of the YAML file containing the techniques administration
    :param output_filename: the output filename defined by the user
    :return:
    """
    # pylint: disable=unused-variable
    my_techniques, name, platform, domain = load_techniques(filename)
    my_techniques = dict(sorted(my_techniques.items(), key=lambda kv: kv[0], reverse=False))
    mitre_techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH_ENTERPRISE if domain ==
                                        'enterprise-attack' else DATA_TYPE_STIX_ALL_TECH_ICS if domain == 'ics-attack' else DATA_TYPE_STIX_ALL_TECH_MOBILE)

    if not output_filename:
        output_filename = 'techniques'
    elif output_filename.endswith('.xlsx'):
        output_filename = output_filename.replace('.xlsx', '')
    excel_filename = get_non_existing_filename('output/' + output_filename, 'xlsx')
    workbook = xlsxwriter.Workbook(excel_filename)
    worksheet_detections = workbook.add_worksheet('Detections')
    worksheet_visibility = workbook.add_worksheet('Visibility')

    # Formatting:
    format_bold_left = workbook.add_format({'align': 'left', 'bold': True})
    format_title = workbook.add_format({'align': 'left', 'bold': True, 'font_size': '14'})
    format_bold_center_bggrey = workbook.add_format({'align': 'center', 'bold': True, 'bg_color': '#dbdbdb'})
    format_bold_center_bgreen = workbook.add_format({'align': 'center', 'bold': True, 'bg_color': '#8bc34a'})
    format_bold_center_bgblue = workbook.add_format({'align': 'center', 'bold': True, 'bg_color': '#64b5f6'})
    wrap_text = workbook.add_format({'text_wrap': True, 'valign': 'top'})
    valign_top = workbook.add_format({'valign': 'top'})
    no_score = workbook.add_format({'valign': 'top', 'align': 'center'})
    detection_score_0 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_0})
    detection_score_1 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_1})
    detection_score_2 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_2})
    detection_score_3 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_3})
    detection_score_4 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_4, 'font_color': '#ffffff'})
    detection_score_5 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_D_5, 'font_color': '#ffffff'})
    visibility_score_1 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_V_1})
    visibility_score_2 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_V_2})
    visibility_score_3 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_V_3, 'font_color': '#ffffff'})
    visibility_score_4 = workbook.add_format({'valign': 'top', 'align': 'center', 'bg_color': COLOR_V_4, 'font_color': '#ffffff'})

    # Title
    worksheet_detections.write(0, 0, 'Overview of detections for ' + name, format_title)
    worksheet_visibility.write(0, 0, 'Overview of visibility for ' + name, format_title)
    worksheet_detections.write(1, 0, 'Domain: ' + domain)
    worksheet_visibility.write(1, 0, 'Domain: ' + domain)
    worksheet_detections.write(2, 0, 'Platform: ' + ', '.join(platform))
    worksheet_visibility.write(2, 0, 'Platform: ' + ', '.join(platform))

    # Header columns
    y = 4
    worksheet_detections.merge_range(y, 0, y, 2, 'Technique', format_bold_center_bggrey)
    worksheet_visibility.merge_range(y, 0, y, 2, 'Technique', format_bold_center_bggrey)
    worksheet_detections.merge_range(y, 3, y, 8, 'Detection', format_bold_center_bgreen)
    worksheet_visibility.merge_range(y, 3, y, 7, 'Visibility', format_bold_center_bgblue)

    # Writing the headers:
    y += 1
    worksheet_detections.write(y, 0, 'ID', format_bold_left)
    worksheet_detections.write(y, 1, 'Description', format_bold_left)
    worksheet_detections.write(y, 2, 'Tactic', format_bold_left)
    worksheet_detections.write(y, 3, 'Applicable to', format_bold_left)
    worksheet_detections.write(y, 4, 'Date', format_bold_left)
    worksheet_detections.write(y, 5, 'Score', format_bold_left)
    worksheet_detections.write(y, 6, 'Location', format_bold_left)
    worksheet_detections.write(y, 7, 'Technique comment', format_bold_left)
    worksheet_detections.write(y, 8, 'Detection comment', format_bold_left)
    worksheet_visibility.write(y, 0, 'ID', format_bold_left)
    worksheet_visibility.write(y, 1, 'Description', format_bold_left)
    worksheet_visibility.write(y, 2, 'Tactic', format_bold_left)
    worksheet_visibility.write(y, 3, 'Applicable to', format_bold_left)
    worksheet_visibility.write(y, 4, 'Date', format_bold_left)
    worksheet_visibility.write(y, 5, 'Score', format_bold_left)
    worksheet_visibility.write(y, 6, 'Technique comment', format_bold_left)
    worksheet_visibility.write(y, 7, 'Visibility comment', format_bold_left)

    worksheet_detections.autofilter(y, 0, y, 8)
    worksheet_visibility.autofilter(y, 0, y, 7)
    worksheet_detections.freeze_panes(y + 1, 0)
    worksheet_visibility.freeze_panes(y + 1, 0)

    worksheet_detections.set_column(0, 0, 8)
    worksheet_detections.set_column(1, 1, 40)
    worksheet_detections.set_column(2, 2, 40)
    worksheet_detections.set_column(3, 3, 18)
    worksheet_detections.set_column(4, 4, 11)
    worksheet_detections.set_column(5, 5, 8)
    worksheet_detections.set_column(6, 8, 50)
    worksheet_visibility.set_column(0, 0, 8)
    worksheet_visibility.set_column(1, 1, 40)
    worksheet_visibility.set_column(2, 2, 40)
    worksheet_visibility.set_column(3, 3, 18)
    worksheet_visibility.set_column(4, 4, 11)
    worksheet_visibility.set_column(5, 5, 8)
    worksheet_visibility.set_column(6, 7, 50)

    dy = y + 1
    for technique_id, technique_data in my_techniques.items():
        # Add row for every detection that is defined:
        for detection in technique_data['detection']:
            worksheet_detections.write(dy, 0, technique_id, valign_top)

            technique = get_technique(mitre_techniques, technique_id)
            if technique is not None:
                worksheet_detections.write(dy, 1, technique['name'], valign_top)
                worksheet_detections.write(dy, 2, ', '.join(t.capitalize() for t in
                                                            get_tactics(technique)),
                                           valign_top)
                worksheet_detections.write(dy, 3, ', '.join(detection['applicable_to']), wrap_text)
                # make sure the date format is '%Y-%m-%d'. When we've done a EQL query this will become '%Y-%m-%d %H %M $%S'
                tmp_date = get_latest_date(detection)
                if isinstance(tmp_date, datetime):
                    tmp_date = tmp_date.strftime('%Y-%m-%d')
                worksheet_detections.write(dy, 4, str(tmp_date).replace('None', ''), valign_top)
                ds = get_latest_score(detection)
                worksheet_detections.write(dy, 5, ds, detection_score_0 if ds == 0 else detection_score_1 if ds == 1 else detection_score_2 if ds == 2 else detection_score_3 if ds == 3 else detection_score_4 if ds == 4 else detection_score_5 if ds == 5 else no_score)  # noqa
                worksheet_detections.write(dy, 6, '\n'.join(detection['location']), wrap_text)
                worksheet_detections.write(dy, 7, detection['comment'][:-1]
                                           if detection['comment'].endswith('\n') else detection['comment'], wrap_text)
                d_comment = get_latest_comment(detection)
                worksheet_detections.write(dy, 8, d_comment[:-1] if d_comment.endswith('\n') else d_comment, wrap_text)
                dy += 1
            else:
                print('[!] Technique ' + technique_id + ' is unknown in ATT&CK. Ignoring this technique.')

    # Writing the visibility items:
    vy = y + 1
    for technique_id, technique_data in my_techniques.items():
        # Add row for every visibility that is defined:
        for visibility in technique_data['visibility']:
            worksheet_visibility.write(vy, 0, technique_id, valign_top)

            technique = get_technique(mitre_techniques, technique_id)
            if technique is not None:
                worksheet_visibility.write(vy, 1, technique['name'], valign_top)
                worksheet_visibility.write(vy, 2, ', '.join(t.capitalize() for t in
                                                            get_tactics(technique)), valign_top)
                worksheet_visibility.write(vy, 3, ', '.join(visibility['applicable_to']), wrap_text)
                # make sure the date format is '%Y-%m-%d'. When we've done a EQL query this will become '%Y-%m-%d %H %M $%S'
                tmp_date = get_latest_date(visibility)
                if isinstance(tmp_date, datetime):
                    tmp_date = tmp_date.strftime('%Y-%m-%d')
                worksheet_visibility.write(vy, 4, str(tmp_date).replace('None', ''), valign_top)
                vs = get_latest_score(visibility)
                worksheet_visibility.write(vy, 5, vs, visibility_score_1 if vs == 1 else visibility_score_2 if vs == 2 else visibility_score_3 if vs == 3 else visibility_score_4 if vs == 4 else no_score)  # noqa
                v_comment = get_latest_comment(visibility)
                worksheet_visibility.write(vy, 6, visibility['comment'][:-1]
                                           if visibility['comment'].endswith('\n') else visibility['comment'], wrap_text)
                worksheet_visibility.write(vy, 7, v_comment[:-1] if v_comment.endswith('\n') else v_comment, wrap_text)
                vy += 1
            else:
                print('[!] Technique ' + technique_id + ' is unknown in ATT&CK. Ignoring this technique.')

    try:
        workbook.close()
        print("File written:   " + excel_filename)
    except Exception as e:
        print('[!] Error while writing Excel file: %s' % str(e))