Mapped data sources to platforms
Marcus Bakker
parent
10f2c4bfd5
commit
363beab8a5
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@ -1,7 +1,7 @@
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<img src="https://github.com/rabobank-cdc/DeTTECT/wiki/images/logo.png" alt="DeTT&CT" width=30% height=30%>
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#### Detect Tactics, Techniques & Combat Threats
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Latest version: [1.2.6](https://github.com/rabobank-cdc/DeTTECT/wiki/Changelog#version-126)
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Latest version: [1.2.7](https://github.com/rabobank-cdc/DeTTECT/wiki/Changelog#version-127)
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To get started with DeTT&CT, check out this [page](https://github.com/rabobank-cdc/DeTTECT/wiki/Getting-started), our [talk](https://www.youtube.com/watch?v=_kWpekkhomU) at hack.lu 2019 and our blog on:
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- [mbsecure.nl/blog/2019/5/dettact-mapping-your-blue-team-to-mitre-attack](https://www.mbsecure.nl/blog/2019/5/dettact-mapping-your-blue-team-to-mitre-attack) or
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42
constants.py
42
constants.py
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@ -2,7 +2,7 @@ import re
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APP_NAME = 'DeTT&CT'
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APP_DESC = 'Detect Tactics, Techniques & Combat Threats'
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VERSION = '1.2.6'
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VERSION = '1.2.7'
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EXPIRE_TIME = 60 * 60 * 24
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@ -131,6 +131,7 @@ YAML_OBJ_VISIBILITY = {'applicable_to': ['all'],
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'auto_generated': True}
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]
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}
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YAML_OBJ_DETECTION = {'applicable_to': ['all'],
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'location': [''],
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'comment': '',
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@ -175,3 +176,42 @@ HEALTH_ERROR_TXT = '[!] The below YAML file contains possible errors. It\'s reco
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PLATFORMS = {'windows': 'Windows', 'linux': 'Linux', 'macos': 'macOS', 'aws': 'AWS', 'gcp': 'GCP', 'azure': 'Azure',
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'azure ad': 'Azure AD', 'office 365': 'Office 365', 'saas': 'SaaS'}
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# Data sources applicable per platform
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DATA_SOURCES = {'Windows': ['Access tokens', 'Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'Binary file metadata', 'BIOS', 'Browser extensions',
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'Component firmware', 'Data loss prevention', 'Detonation chamber', 'Digital certificate logs', 'Disk forensics', 'DLL monitoring', 'DNS records', 'EFI', 'Email gateway',
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'Environment variable', 'File monitoring', 'Host network interface', 'Kernel drivers', 'Loaded DLLs', 'Mail server', 'Malware reverse engineering', 'MBR', 'Named Pipes',
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'Netflow/Enclave netflow', 'Network device logs', 'Network intrusion detection system', 'Network protocol analysis', 'Packet capture', 'PowerShell logs',
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'Process command-line parameters', 'Process monitoring', 'Process use of network', 'Sensor health and status', 'Services', 'SSL/TLS inspection', 'System calls',
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'Third-party application logs', 'User interface', 'VBR', 'Web application firewall logs', 'Web logs', 'Web proxy', 'Windows Error Reporting', 'Windows event logs',
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'Windows Registry', 'WMI Objects'],
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'Linux': ['Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'Binary file metadata', 'BIOS', 'Browser extensions', 'Component firmware',
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'Data loss prevention', 'Detonation chamber', 'Digital certificate logs', 'Disk forensics', 'DNS records', 'EFI', 'Email gateway', 'Environment variable', 'File monitoring',
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'Host network interface', 'Kernel drivers', 'Mail server', 'Malware reverse engineering', 'MBR', 'Named Pipes', 'Netflow/Enclave netflow', 'Network device logs',
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'Network intrusion detection system', 'Network protocol analysis', 'Packet capture', 'PowerShell logs', 'Process command-line parameters', 'Process monitoring',
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'Process use of network', 'Sensor health and status', 'Services', 'SSL/TLS inspection', 'System calls', 'Third-party application logs', 'User interface', 'VBR',
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'Web application firewall logs', 'Web logs', 'Web proxy'],
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'macOS': ['Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'Binary file metadata', 'BIOS', 'Browser extensions', 'Component firmware',
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'Data loss prevention', 'Detonation chamber', 'Digital certificate logs', 'Disk forensics', 'DNS records', 'EFI', 'Email gateway', 'Environment variable', 'File monitoring',
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'Host network interface', 'Kernel drivers', 'Mail server', 'Malware reverse engineering', 'MBR', 'Named Pipes', 'Netflow/Enclave netflow', 'Network device logs',
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'Network intrusion detection system', 'Network protocol analysis', 'Packet capture', 'PowerShell logs', 'Process command-line parameters', 'Process monitoring',
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'Process use of network', 'Sensor health and status', 'Services', 'SSL/TLS inspection', 'System calls', 'Third-party application logs', 'User interface', 'VBR',
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'Web application firewall logs', 'Web logs', 'Web proxy'],
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'AWS': ['Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'AWS CloudTrail logs', 'AWS OS logs', 'Binary file metadata', 'Data loss prevention',
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'Detonation chamber', 'DNS records', 'Email gateway', 'File monitoring', 'Mail server', 'Malware reverse engineering', 'Netflow/Enclave netflow', 'Network device logs',
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'Network intrusion detection system', 'Network protocol analysis', 'Packet capture', 'Sensor health and status', 'SSL/TLS inspection', 'Third-party application logs',
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'Web application firewall logs', 'Web logs', 'Web proxy'],
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'GCP': ['Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'Binary file metadata', 'Data loss prevention', 'Detonation chamber',
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'DNS records', 'Email gateway', 'File monitoring', 'Mail server', 'Malware reverse engineering', 'Netflow/Enclave netflow', 'Network device logs',
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'Network intrusion detection system', 'Network protocol analysis', 'Packet capture', 'Sensor health and status', 'SSL/TLS inspection', 'Stackdriver logs',
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'Third-party application logs', 'Web application firewall logs', 'Web logs', 'Web proxy'],
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'Azure': ['Anti-virus', 'API monitoring', 'Application logs', 'Asset management', 'Authentication logs', 'Azure activity logs', 'Azure OS logs', 'Binary file metadata',
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'Data loss prevention', 'DNS records', 'File monitoring', 'Malware reverse engineering', 'Netflow/Enclave netflow', 'Network device logs', 'Network intrusion detection system',
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'Network protocol analysis', 'Packet capture', 'Sensor health and status', 'SSL/TLS inspection', 'Third-party application logs', 'Web application firewall logs',
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'Web logs', 'Web proxy'],
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'Azure AD': ['API monitoring', 'Authentication logs', 'Azure activity logs', 'Malware reverse engineering', 'Sensor health and status'],
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'Office 365': ['Anti-virus', 'API monitoring', 'Authentication logs', 'Azure activity logs', 'Data loss prevention', 'Detonation chamber', 'Email gateway', 'Mail server',
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'Malware reverse engineering', 'Office 365 account logs', 'Office 365 audit logs', 'Office 365 trace logs', 'Sensor health and status'],
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'Saas': ['Anti-virus', 'API monitoring', 'Application logs', 'Authentication logs', 'Data loss prevention', 'Detonation chamber', 'Email gateway', 'Mail server',
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'Malware reverse engineering', 'OAuth audit logs', 'Sensor health and status', 'Third-party application logs', 'Web application firewall logs', 'Web logs']
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}
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@ -1,7 +1,7 @@
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from copy import deepcopy
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from datetime import datetime
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import simplejson
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import xlsxwriter
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import simplejson
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from generic import *
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@ -17,7 +17,7 @@ def generate_data_sources_layer(filename):
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my_data_sources, name, platform, exceptions = _load_data_sources(filename)
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# Do the mapping between my data sources and MITRE data sources:
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my_techniques = _map_and_colorize_techniques(my_data_sources, exceptions)
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my_techniques = _map_and_colorize_techniques(my_data_sources, platform, exceptions)
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layer = get_layer_template_data_sources("Data sources " + name, 'description', 'attack', platform)
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layer['techniques'] = my_techniques
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@ -66,7 +66,7 @@ def export_data_source_list_to_excel(filename, eql_search=False):
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:return:
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"""
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# pylint: disable=unused-variable
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my_data_sources, name, platform, exceptions = _load_data_sources(filename, filter_empty_scores=False)
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my_data_sources, name, platforms, exceptions = _load_data_sources(filename, filter_empty_scores=False)
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excel_filename = get_non_existing_filename('output/data_sources', 'xlsx')
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workbook = xlsxwriter.Workbook(excel_filename)
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@ -121,7 +121,9 @@ def export_data_source_list_to_excel(filename, eql_search=False):
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ds_miss_text = 'ATT&CK data source is missing from the YAML file'
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# pylint: disable=consider-iterating-dictionary
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my_ds_list = [ds.lower() for ds in my_data_sources.keys()]
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for ds in get_all_mitre_data_sources():
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applicable_data_sources = get_applicable_data_sources_platform(platforms)
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for ds in applicable_data_sources:
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if ds.lower() not in my_ds_list:
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ds_obj = deepcopy(YAML_OBJ_DATA_SOURCE)
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ds_obj['data_source_name'] = ds
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@ -159,7 +161,7 @@ def export_data_source_list_to_excel(filename, eql_search=False):
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if score > 0:
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score = score / score_count
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worksheet.write(y, 11, score, dq_score_1 if score < 2 else dq_score_2 if score < 3 else dq_score_3 if score < 4 else dq_score_4 if score < 5 else dq_score_5 if score < 6 else no_score)
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worksheet.write(y, 11, score, dq_score_1 if score < 2 else dq_score_2 if score < 3 else dq_score_3 if score < 4 else dq_score_4 if score < 5 else dq_score_5 if score < 6 else no_score) # noqa
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y += 1
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worksheet.autofilter(2, 0, 2, 11)
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@ -207,22 +209,40 @@ def _load_data_sources(file, filter_empty_scores=True):
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return my_data_sources, name, platform, exceptions
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def _map_and_colorize_techniques(my_ds, exceptions):
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def _count_applicable_data_sources(technique, applicable_data_sources):
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"""
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get the count of applicable data sources for the provided technique.
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This takes into account which data sources are applicable for a platform(s)
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:param technique: ATT&CK CTI technique object
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:param applicable_data_sources: a list of applicable ATT&CK data sources
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:return: a count of the applicable data sources for this technique
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"""
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applicable_ds_count = 0
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for ds in technique['x_mitre_data_sources']:
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if ds in applicable_data_sources:
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applicable_ds_count += 1
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return applicable_ds_count
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def _map_and_colorize_techniques(my_ds, platforms, exceptions):
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"""
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Determine the color of the techniques based on how many data sources are available per technique.
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:param my_ds: the configured data sources
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:param platforms: the configured platform(s)
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:param exceptions: the list of ATT&CK technique exception within the data source YAML file
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:return: a dictionary with techniques that can be used in the layer's output file
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"""
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techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH)
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applicable_data_sources = get_applicable_data_sources_platform(platforms)
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technique_colors = {}
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# Color the techniques based on how many data sources are available.
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for t in techniques:
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if 'x_mitre_data_sources' in t:
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total_ds_count = len(t['x_mitre_data_sources'])
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total_ds_count = _count_applicable_data_sources(t, applicable_data_sources)
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ds_count = 0
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for ds in t['x_mitre_data_sources']:
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if ds in my_ds.keys():
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if ds in my_ds.keys() and ds in applicable_data_sources:
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ds_count += 1
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if total_ds_count > 0:
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result = (float(ds_count) / float(total_ds_count)) * 100
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@ -234,7 +254,7 @@ def _map_and_colorize_techniques(my_ds, exceptions):
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output_techniques = []
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for t, v in my_techniques.items():
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if t not in exceptions:
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if t not in exceptions and t in technique_colors:
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for tactic in v['tactics']:
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d = dict()
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d['techniqueID'] = t
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@ -243,8 +263,10 @@ def _map_and_colorize_techniques(my_ds, exceptions):
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d['enabled'] = True
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d['tactic'] = tactic.lower().replace(' ', '-')
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d['metadata'] = [{'name': '-Available data sources', 'value': ', '.join(v['my_data_sources'])},
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{'name': '-ATT&CK data sources', 'value': ', '.join(v['data_sources'])},
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{'name': '-ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(v['data_sources'],
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applicable_data_sources))},
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{'name': '-Products', 'value': ', '.join(v['products'])}]
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d['metadata'] = make_layer_metadata_compliant(d['metadata'])
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output_techniques.append(d)
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@ -377,7 +399,8 @@ def update_technique_administration_file(file_data_sources, file_tech_admin):
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# ask how the score should be updated
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answer = 0
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if mix_scores:
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answer = ask_multiple_choice(V_UPDATE_Q_MIXED, [V_UPDATE_ANSWER_3, V_UPDATE_ANSWER_4, V_UPDATE_ANSWER_1, V_UPDATE_ANSWER_2, V_UPDATE_ANSWER_CANCEL])
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answer = ask_multiple_choice(V_UPDATE_Q_MIXED, [V_UPDATE_ANSWER_3, V_UPDATE_ANSWER_4,
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V_UPDATE_ANSWER_1, V_UPDATE_ANSWER_2, V_UPDATE_ANSWER_CANCEL])
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elif manually_scored:
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answer = ask_multiple_choice(V_UPDATE_Q_ALL_MANUAL, [V_UPDATE_ANSWER_1, V_UPDATE_ANSWER_2, V_UPDATE_ANSWER_CANCEL])
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elif auto_scored:
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@ -458,7 +481,7 @@ def update_technique_administration_file(file_data_sources, file_tech_admin):
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print(' - Date: ' + new_score_obj['date'])
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print(' - Score: ' + str(new_score_obj['score']))
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print(' - Visibility comment: ' + _indent_comment(new_score_obj['comment'], 23))
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print(' - Auto generated: true')
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print(' - Auto generated: True')
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print('')
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if ask_yes_no('Update the score?'):
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are_scores_updated = True
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@ -484,6 +507,8 @@ def update_technique_administration_file(file_data_sources, file_tech_admin):
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print('No visibility scores have been updated.')
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# pylint: disable=redefined-outer-name
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def generate_technique_administration_file(filename, write_file=True, all_techniques=False):
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"""
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Generate a technique administration file based on the data source administration YAML file
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@ -496,6 +521,7 @@ def generate_technique_administration_file(filename, write_file=True, all_techni
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my_data_sources, name, platform, exceptions = _load_data_sources(filename)
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techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH_ENTERPRISE)
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applicable_data_sources = get_applicable_data_sources_platform(platform)
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yaml_file = dict()
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yaml_file['version'] = FILE_TYPE_TECHNIQUE_ADMINISTRATION_VERSION
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@ -511,10 +537,10 @@ def generate_technique_administration_file(filename, write_file=True, all_techni
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if platform == 'all' or len(set(platforms).intersection(set(platform))) > 0:
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# not every technique has data source listed
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if 'x_mitre_data_sources' in t:
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total_ds_count = len(t['x_mitre_data_sources'])
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total_ds_count = _count_applicable_data_sources(t, applicable_data_sources)
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ds_count = 0
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for ds in t['x_mitre_data_sources']:
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if ds in my_data_sources.keys():
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if ds in my_data_sources.keys() and ds in applicable_data_sources:
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ds_count += 1
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if total_ds_count > 0:
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result = (float(ds_count) / float(total_ds_count)) * 100
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@ -549,7 +575,8 @@ def generate_technique_administration_file(filename, write_file=True, all_techni
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# remove the single quotes from the date
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yaml_file_lines = fix_date_and_remove_null(file_lines, today, input_type='list')
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output_filename = get_non_existing_filename('output/techniques-administration-' + normalize_name_to_filename(name + '-' + platform_to_name(platform)), 'yaml')
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output_filename = get_non_existing_filename('output/techniques-administration-' +
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normalize_name_to_filename(name + '-' + platform_to_name(platform)), 'yaml')
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with open(output_filename, 'w') as f:
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f.writelines(yaml_file_lines)
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print("File written: " + output_filename)
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53
generic.py
53
generic.py
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@ -2,8 +2,8 @@ import os
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import shutil
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import pickle
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from io import StringIO
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from ruamel.yaml import YAML
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from datetime import datetime as dt
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from ruamel.yaml import YAML
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from upgrade import upgrade_yaml_file
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from constants import *
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from health import check_yaml_file_health
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@ -173,6 +173,10 @@ def load_attack_data(data_type):
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def init_yaml():
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"""
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Initialize ruamel.yaml with the correct settings
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:return: am uamel.yaml object
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"""
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_yaml = YAML()
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_yaml.Representer.ignore_aliases = lambda *args: True # disable anchors/aliases
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return _yaml
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@ -601,6 +605,39 @@ def platform_to_name(platform, separator='-'):
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return ''
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def get_applicable_data_sources_platform(platforms):
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"""
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Get the applicable ATT&CK data sources for the provided platform(s)
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:param platforms: the ATT&CK platform(s)
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:return: a list of applicable ATT&CK data sources
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"""
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applicable_data_sources = set()
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if platforms == 'all' or 'all' in platforms:
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# pylint: disable=unused-variable
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for k, v in DATA_SOURCES.items():
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applicable_data_sources.update(v)
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else:
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for p in platforms:
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applicable_data_sources.update(DATA_SOURCES[p])
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return list(applicable_data_sources)
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def get_applicable_data_sources_technique(technique_data_sources, platform_applicable_data_sources):
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"""
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Get the applicable ATT&CK data sources for the provided technique's data sources (for which the source is ATT&CK CTI)
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:param technique_data_sources: the ATT&CK technique's data sources
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:param platform_applicable_data_sources: a list of applicable ATT&CK data sources based on 'DATA_SOURCES'
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:return: a list of applicable data sources
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"""
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applicable_data_sources = set()
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for ds in technique_data_sources:
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if ds in platform_applicable_data_sources:
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applicable_data_sources.add(ds)
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return list(applicable_data_sources)
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def map_techniques_to_data_sources(techniques, my_data_sources):
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"""
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This function maps the MITRE ATT&CK techniques to your data sources.
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@ -806,6 +843,20 @@ def check_file(filename, file_type=None, health_is_called=False):
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return yaml_content # value is None
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def make_layer_metadata_compliant(metadata):
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"""
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Make sure the metadata values in the Navigator layer file are compliant with the expected data structure
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from the latest version on: https://github.com/mitre-attack/attack-navigator/tree/master/layers
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:param metadata: list of metadata dictionaries
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:return: compliant list of metadata dictionaries
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"""
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for md_item in metadata:
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if not md_item['value'] or md_item['value'] == '':
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md_item['value'] = '-'
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return metadata
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def get_updates(update_type, sort='modified'):
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"""
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Print a list of updates for a techniques, groups or software. Sort by modified or creation date.
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67
health.py
67
health.py
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@ -94,7 +94,7 @@ def check_health_data_sources(filename, ds_content, health_is_called, no_print=F
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ATT&CK Platform is not part of the EQL search result
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:return: False if no errors have been found, otherwise True
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"""
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from generic import get_all_mitre_data_sources
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from generic import get_applicable_data_sources_platform
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has_error = False
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platform = ds_content.get('platform', None)
|
||||
|
|
@ -113,8 +113,8 @@ def check_health_data_sources(filename, ds_content, health_is_called, no_print=F
|
|||
health_is_called)
|
||||
|
||||
ds_list = [kv['data_source_name'].lower() for kv in ds_content['data_sources']]
|
||||
ds_list_mitre = get_all_mitre_data_sources()
|
||||
for ds in ds_list_mitre:
|
||||
applicable_data_sources = get_applicable_data_sources_platform(platform)
|
||||
for ds in applicable_data_sources:
|
||||
if ds.lower() not in ds_list:
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds + '\' is MISSING from the YAML file', health_is_called)
|
||||
|
||||
|
|
@ -122,30 +122,34 @@ def check_health_data_sources(filename, ds_content, health_is_called, no_print=F
|
|||
# check for missing keys
|
||||
for key in ['data_source_name', 'date_registered', 'date_connected', 'products', 'available_for_data_analytics', 'comment', 'data_quality']:
|
||||
if key not in ds:
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' is MISSING a key-value pair: ' + key, health_is_called)
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] +
|
||||
'\' is MISSING a key-value pair: ' + key, health_is_called)
|
||||
|
||||
for key in ['date_registered', 'date_connected']:
|
||||
if key in ds and not ds[key] is None:
|
||||
try:
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
ds[key].year
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
ds[key].month
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
ds[key].day
|
||||
except AttributeError:
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' has an INVALID data format for the dimension \'' + dimension
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' has an INVALID data format for the key-value pair \'' + key
|
||||
+ '\': ' + ds[key] + ' (should be YYYY-MM-DD without quotes)', health_is_called)
|
||||
print(type(ds[key]))
|
||||
|
||||
if 'available_for_data_analytics' in ds:
|
||||
if not isinstance(ds['available_for_data_analytics'], bool):
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' has an INVALID \'available_for_data_analytics\' value: should be set to \'true\' or \'false\'', health_is_called)
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] +
|
||||
'\' has an INVALID \'available_for_data_analytics\' value: should be set to \'true\' or \'false\'', health_is_called)
|
||||
|
||||
if 'data_quality' in ds:
|
||||
if isinstance(ds['data_quality'], dict):
|
||||
for dimension in ['device_completeness', 'data_field_completeness', 'timeliness', 'consistency', 'retention']:
|
||||
if dimension not in ds['data_quality']:
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' is MISSING a key-value pair in \'data_quality\': ' + dimension, health_is_called)
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] +
|
||||
'\' is MISSING a key-value pair in \'data_quality\': ' + dimension, health_is_called)
|
||||
else:
|
||||
if isinstance(ds['data_quality'][dimension], int):
|
||||
if not 0 <= ds['data_quality'][dimension] <= 5:
|
||||
|
|
@ -155,14 +159,16 @@ def check_health_data_sources(filename, ds_content, health_is_called, no_print=F
|
|||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' has an INVALID data quality score for the dimension \'' +
|
||||
dimension + '\': ' + str(ds['data_quality'][dimension]) + ' (should be an an integer)', health_is_called)
|
||||
else:
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] + '\' the key-value pair \'data_quality\' is NOT a dictionary with data quality dimension scores', health_is_called)
|
||||
has_error = _print_error_msg('[!] Data source: \'' + ds['data_source_name'] +
|
||||
'\' the key-value pair \'data_quality\' is NOT a dictionary with data quality dimension scores', health_is_called)
|
||||
|
||||
if 'exceptions' in ds_content:
|
||||
for tech in ds_content['exceptions']:
|
||||
tech_id = str(tech['technique_id'])
|
||||
|
||||
if not REGEX_YAML_TECHNIQUE_ID_FORMAT.match(tech_id) and tech_id != 'None':
|
||||
has_error = _print_error_msg('[!] INVALID technique ID in the \'exceptions\' list of data source admin. file: ' + tech_id, health_is_called)
|
||||
has_error = _print_error_msg(
|
||||
'[!] INVALID technique ID in the \'exceptions\' list of data source admin. file: ' + tech_id, health_is_called)
|
||||
|
||||
if has_error and not health_is_called and not no_print:
|
||||
print(HEALTH_ERROR_TXT + filename)
|
||||
|
|
@ -199,13 +205,16 @@ def _check_health_score_object(yaml_object, object_type, tech_id, health_is_call
|
|||
for score_obj in yaml_object['score_logbook']:
|
||||
for key in ['date', 'score', 'comment']:
|
||||
if key not in score_obj:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' is MISSING a key-value pair in a ' + object_type + ' score object within the \'score_logbook\': ' + key, health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' is MISSING a key-value pair in a ' +
|
||||
object_type + ' score object within the \'score_logbook\': ' + key, health_is_called)
|
||||
|
||||
if score_obj['score'] is None:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an EMPTY key-value pair in a ' + object_type + ' score object within the \'score_logbook\': score', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an EMPTY key-value pair in a ' +
|
||||
object_type + ' score object within the \'score_logbook\': score', health_is_called)
|
||||
|
||||
elif not isinstance(score_obj['score'], int):
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an INVALID score format in a ' + object_type + ' score object within the \'score_logbook\': ' + score_obj['score'] + ' (should be an integer)', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an INVALID score format in a ' + object_type +
|
||||
' score object within the \'score_logbook\': ' + score_obj['score'] + ' (should be an integer)', health_is_called)
|
||||
|
||||
if 'auto_generated' in score_obj:
|
||||
if not isinstance(score_obj['auto_generated'], bool):
|
||||
|
|
@ -214,23 +223,24 @@ def _check_health_score_object(yaml_object, object_type, tech_id, health_is_call
|
|||
|
||||
if isinstance(score_obj['score'], int):
|
||||
if score_obj['date'] is None and ((score_obj['score'] > -1 and object_type == 'detection') or (score_obj['score'] > 0 and object_type == 'visibility')):
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an EMPTY key-value pair in a ' + object_type + ' score object within the \'score_logbook\': date', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an EMPTY key-value pair in a ' +
|
||||
object_type + ' score object within the \'score_logbook\': date', health_is_called)
|
||||
|
||||
# noinspection PyChainedComparisons
|
||||
if not (score_obj['score'] >= min_score and score_obj['score'] <= max_score):
|
||||
has_error = _print_error_msg(
|
||||
'[!] Technique ID: ' + tech_id + ' has an INVALID ' + object_type + ' score in a score object within the \'score_logbook\': ' + str(score_obj['score']) + ' (should be between ' + str(min_score) + ' and ' + str(max_score) + ')', health_is_called)
|
||||
|
||||
if not score_obj['date'] is None:
|
||||
try:
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
score_obj['date'].year
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
score_obj['date'].month
|
||||
# noinspection PyStatementEffect
|
||||
# pylint: disable=pointless-statement
|
||||
score_obj['date'].day
|
||||
except AttributeError:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an INVALID data format in a ' + object_type + ' score object within the \'score_logbook\': ' + score_obj['date'] + ' (should be YYYY-MM-DD without quotes)', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech_id + ' has an INVALID data format in a ' + object_type +
|
||||
' score object within the \'score_logbook\': ' + score_obj['date'] + ' (should be YYYY-MM-DD without quotes)', health_is_called)
|
||||
except KeyError:
|
||||
pass
|
||||
|
||||
|
|
@ -296,12 +306,14 @@ def _check_health_techniques(filename, technique_content, health_is_called):
|
|||
|
||||
for okey in obj_keys:
|
||||
if okey not in obj:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' is MISSING a key-value pair in \'' + obj_type + '\': ' + okey, health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech +
|
||||
' is MISSING a key-value pair in \'' + obj_type + '\': ' + okey, health_is_called)
|
||||
|
||||
for okey in obj_keys_list:
|
||||
if okey in obj:
|
||||
if not isinstance(obj[okey], list):
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey + '\' in \'' + obj_type + '\' is NOT a list', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey +
|
||||
'\' in \'' + obj_type + '\' is NOT a list', health_is_called)
|
||||
|
||||
for okey in obj_keys_not_none:
|
||||
if okey in obj:
|
||||
|
|
@ -310,9 +322,11 @@ def _check_health_techniques(filename, technique_content, health_is_called):
|
|||
if item is None:
|
||||
none_count += 1
|
||||
if none_count == 1:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey + '\' in \'' + obj_type + '\' has an EMPTY value (an empty string is allowed: \'\')', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey + '\' in \'' +
|
||||
obj_type + '\' has an EMPTY value (an empty string is allowed: \'\')', health_is_called)
|
||||
elif none_count > 1:
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey + '\' in \'' + obj_type + '\' has multiple EMPTY values (an empty string is allowed: \'\')', health_is_called)
|
||||
has_error = _print_error_msg('[!] Technique ID: ' + tech + ' the key-value pair \'' + okey + '\' in \'' + obj_type +
|
||||
'\' has multiple EMPTY values (an empty string is allowed: \'\')', health_is_called)
|
||||
|
||||
health = _check_health_score_object(obj, obj_type, tech, health_is_called)
|
||||
has_error = _update_health_state(has_error, health)
|
||||
|
|
@ -330,7 +344,8 @@ def _check_health_techniques(filename, technique_content, health_is_called):
|
|||
similar.add(i2)
|
||||
|
||||
if len(similar) > 0:
|
||||
has_error = _print_error_msg('[!] There are values in the key-value pairs for \'applicable_to\' which are very similar. Correct where necessary:', health_is_called)
|
||||
has_error = _print_error_msg(
|
||||
'[!] There are values in the key-value pairs for \'applicable_to\' which are very similar. Correct where necessary:', health_is_called)
|
||||
for s in similar:
|
||||
_print_error_msg(' - ' + s, health_is_called)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import simplejson
|
||||
from generic import *
|
||||
import xlsxwriter
|
||||
from generic import *
|
||||
from datetime import datetime
|
||||
# Imports for pandas and plotly are because of performance reasons in the function that uses these libraries.
|
||||
|
||||
|
|
@ -21,7 +21,7 @@ def generate_detection_layer(filename_techniques, filename_data_sources, overlay
|
|||
else:
|
||||
my_techniques, name, platform = load_techniques(filename_techniques)
|
||||
my_data_sources = _load_data_sources(filename_data_sources)
|
||||
mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources)
|
||||
mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources, platform)
|
||||
layer_both = get_layer_template_layered('Visibility and Detection ' + name, 'description', 'attack', platform)
|
||||
_write_layer(layer_both, mapped_techniques_both, 'visibility_and_detection', name)
|
||||
|
||||
|
|
@ -38,28 +38,29 @@ def generate_visibility_layer(filename_techniques, filename_data_sources, overla
|
|||
|
||||
if not overlay:
|
||||
my_techniques, name, platform = load_techniques(filename_techniques)
|
||||
mapped_techniques_visibility = _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources)
|
||||
mapped_techniques_visibility = _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources, platform)
|
||||
layer_visibility = get_layer_template_visibility('Visibility ' + name, 'description', 'attack', platform)
|
||||
_write_layer(layer_visibility, mapped_techniques_visibility, 'visibility', name)
|
||||
else:
|
||||
my_techniques, name, platform = load_techniques(filename_techniques)
|
||||
mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources)
|
||||
mapped_techniques_both = _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources, platform)
|
||||
layer_both = get_layer_template_layered('Visibility and Detection ' + name, 'description', 'attack', platform)
|
||||
_write_layer(layer_both, mapped_techniques_both, 'visibility_and_detection', name)
|
||||
|
||||
|
||||
def plot_graph(filename, type):
|
||||
def plot_graph(filename, type_graph):
|
||||
"""
|
||||
Generates a line graph which shows the improvements on detections through the time.
|
||||
:param filename: the filename of the YAML file containing the techniques administration
|
||||
:param type: indicates the type of the graph: detection or visibility
|
||||
:param type_graph: indicates the type of the graph: detection or visibility
|
||||
:return:
|
||||
"""
|
||||
# pylint: disable=unused-variable
|
||||
my_techniques, name, platform = load_techniques(filename)
|
||||
|
||||
graph_values = []
|
||||
for t in my_techniques.values():
|
||||
for item in t[type]:
|
||||
for item in t[type_graph]:
|
||||
date = get_latest_date(item)
|
||||
if date:
|
||||
yyyymm = date.strftime('%Y-%m')
|
||||
|
|
@ -69,13 +70,13 @@ def plot_graph(filename, type):
|
|||
df = pd.DataFrame(graph_values).groupby('date', as_index=False)[['count']].sum()
|
||||
df['cumcount'] = df['count'].cumsum()
|
||||
|
||||
output_filename = get_non_existing_filename('output/graph_%s' % type, 'html')
|
||||
output_filename = get_non_existing_filename('output/graph_%s' % type_graph, '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, name))},
|
||||
'layout': go.Layout(title="# of %s items for %s" % (type_graph, name))},
|
||||
filename=output_filename, auto_open=False
|
||||
)
|
||||
print("File written: " + output_filename)
|
||||
|
|
@ -122,20 +123,6 @@ def _write_layer(layer, mapped_techniques, filename_prefix, name):
|
|||
write_file(filename_prefix, name, json_string)
|
||||
|
||||
|
||||
def _layer_metadata_make_compliant(metadata):
|
||||
"""
|
||||
Make sure the metadata values in the Navigator layer file are compliant with the expected data structure
|
||||
from the latest version on: https://github.com/mitre-attack/attack-navigator/tree/master/layers
|
||||
:param metadata: list of metadata dictionaries
|
||||
:return: compliant list of metadata dictionaries
|
||||
"""
|
||||
for md_item in metadata:
|
||||
if not md_item['value'] or md_item['value'] == '':
|
||||
md_item['value'] = '-'
|
||||
|
||||
return metadata
|
||||
|
||||
|
||||
def _map_and_colorize_techniques_for_detections(my_techniques):
|
||||
"""
|
||||
Determine the color of the techniques based on the detection score in the given YAML file.
|
||||
|
|
@ -180,7 +167,7 @@ def _map_and_colorize_techniques_for_detections(my_techniques):
|
|||
if cnt != tcnt:
|
||||
x['metadata'].append({'name': '---', 'value': '---'})
|
||||
cnt += 1
|
||||
x['metadata'] = _layer_metadata_make_compliant(x['metadata'])
|
||||
x['metadata'] = make_layer_metadata_compliant(x['metadata'])
|
||||
mapped_techniques.append(x)
|
||||
except Exception as e:
|
||||
print('[!] Possible error in YAML file at: %s. Error: %s' % (technique_id, str(e)))
|
||||
|
|
@ -189,14 +176,16 @@ def _map_and_colorize_techniques_for_detections(my_techniques):
|
|||
return mapped_techniques
|
||||
|
||||
|
||||
def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources):
|
||||
def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources, platforms):
|
||||
"""
|
||||
Determine the color of the techniques based on the visibility score in the given YAML file.
|
||||
:param my_techniques: the configured techniques
|
||||
:param my_data_sources: the configured data sources
|
||||
:param platforms: the configured platform(s)
|
||||
:return: a dictionary with techniques that can be used in the layer's output file
|
||||
"""
|
||||
techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH)
|
||||
applicable_data_sources = get_applicable_data_sources_platform(platforms)
|
||||
|
||||
technique_ds_mapping = map_techniques_to_data_sources(techniques, my_data_sources)
|
||||
|
||||
|
|
@ -208,7 +197,7 @@ def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources):
|
|||
if s == 0:
|
||||
s = None
|
||||
|
||||
my_ds = ', '.join(technique_ds_mapping[technique_id]['my_data_sources']) if technique_id in technique_ds_mapping.keys() and technique_ds_mapping[technique_id]['my_data_sources'] else ''
|
||||
my_ds = ', '.join(technique_ds_mapping[technique_id]['my_data_sources']) if technique_id in technique_ds_mapping.keys() and technique_ds_mapping[technique_id]['my_data_sources'] else '' # noqa
|
||||
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 ''
|
||||
|
||||
|
|
@ -221,7 +210,8 @@ def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources):
|
|||
x['tactic'] = tactic.lower().replace(' ', '-')
|
||||
x['metadata'] = []
|
||||
x['metadata'].append({'name': '-Available data sources', 'value': my_ds})
|
||||
x['metadata'].append({'name': '-ATT&CK data sources', 'value': ', '.join(technique['x_mitre_data_sources'])})
|
||||
x['metadata'].append({'name': '-ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(technique['x_mitre_data_sources'],
|
||||
applicable_data_sources))})
|
||||
x['metadata'].append({'name': '---', 'value': '---'})
|
||||
x['score'] = s
|
||||
|
||||
|
|
@ -237,7 +227,7 @@ def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources):
|
|||
x['metadata'].append({'name': '---', 'value': '---'})
|
||||
cnt += 1
|
||||
|
||||
x['metadata'] = _layer_metadata_make_compliant(x['metadata'])
|
||||
x['metadata'] = make_layer_metadata_compliant(x['metadata'])
|
||||
mapped_techniques.append(x)
|
||||
|
||||
for t in techniques:
|
||||
|
|
@ -251,23 +241,25 @@ def _map_and_colorize_techniques_for_visibility(my_techniques, my_data_sources):
|
|||
x['comment'] = ''
|
||||
x['enabled'] = True
|
||||
x['tactic'] = tactic.lower().replace(' ', '-')
|
||||
ds = ', '.join(t['x_mitre_data_sources']) if 'x_mitre_data_sources' in t else ''
|
||||
ds = ', '.join(get_applicable_data_sources_technique(t['x_mitre_data_sources'], applicable_data_sources)) if 'x_mitre_data_sources' in t else '' # noqa
|
||||
x['metadata'] = [{'name': '-ATT&CK data sources', 'value': ds}]
|
||||
|
||||
x['metadata'] = _layer_metadata_make_compliant(x['metadata'])
|
||||
x['metadata'] = make_layer_metadata_compliant(x['metadata'])
|
||||
mapped_techniques.append(x)
|
||||
|
||||
return mapped_techniques
|
||||
|
||||
|
||||
def _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources):
|
||||
def _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources, platforms):
|
||||
"""
|
||||
Determine the color of the techniques based on both detection and visibility.
|
||||
:param my_techniques: the configured techniques
|
||||
:param my_data_sources: the configured data sources
|
||||
:param platforms: the configured platform(s)
|
||||
:return: a dictionary with techniques that can be used in the layer's output file
|
||||
"""
|
||||
techniques = load_attack_data(DATA_TYPE_STIX_ALL_TECH)
|
||||
applicable_data_sources = get_applicable_data_sources_platform(platforms)
|
||||
|
||||
technique_ds_mapping = map_techniques_to_data_sources(techniques, my_data_sources)
|
||||
|
||||
|
|
@ -290,7 +282,7 @@ def _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources):
|
|||
else:
|
||||
color = COLOR_WHITE
|
||||
|
||||
my_ds = ', '.join(technique_ds_mapping[technique_id]['my_data_sources']) if technique_id in technique_ds_mapping.keys() and technique_ds_mapping[technique_id]['my_data_sources'] else ''
|
||||
my_ds = ', '.join(technique_ds_mapping[technique_id]['my_data_sources']) if technique_id in technique_ds_mapping.keys() and technique_ds_mapping[technique_id]['my_data_sources'] else '' # noqa
|
||||
|
||||
technique = get_technique(techniques, technique_id)
|
||||
for tactic in get_tactics(technique):
|
||||
|
|
@ -302,7 +294,8 @@ def _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources):
|
|||
x['tactic'] = tactic.lower().replace(' ', '-')
|
||||
x['metadata'] = []
|
||||
x['metadata'].append({'name': '-Available data sources', 'value': my_ds})
|
||||
x['metadata'].append({'name': '-ATT&CK data sources', 'value': ', '.join(technique['x_mitre_data_sources'])})
|
||||
x['metadata'].append({'name': '-ATT&CK data sources', 'value': ', '.join(get_applicable_data_sources_technique(technique['x_mitre_data_sources'],
|
||||
applicable_data_sources))})
|
||||
x['metadata'].append({'name': '---', 'value': '---'})
|
||||
|
||||
# Metadata for detection:
|
||||
|
|
@ -337,7 +330,7 @@ def _map_and_colorize_techniques_for_overlaid(my_techniques, my_data_sources):
|
|||
x['metadata'].append({'name': '---', 'value': '---'})
|
||||
cnt += 1
|
||||
|
||||
x['metadata'] = _layer_metadata_make_compliant(x['metadata'])
|
||||
x['metadata'] = make_layer_metadata_compliant(x['metadata'])
|
||||
mapped_techniques.append(x)
|
||||
|
||||
return mapped_techniques
|
||||
|
|
@ -349,6 +342,7 @@ def export_techniques_list_to_excel(filename):
|
|||
:param filename: the filename of the YAML file containing the techniques administration
|
||||
:return:
|
||||
"""
|
||||
# pylint: disable=unused-variable
|
||||
my_techniques, name, platform = 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)
|
||||
|
|
@ -422,7 +416,7 @@ def export_techniques_list_to_excel(filename):
|
|||
tmp_date = tmp_date.strftime('%Y-%m-%d')
|
||||
worksheet_detections.write(y, 4, str(tmp_date).replace('None', ''), valign_top)
|
||||
ds = get_latest_score(detection)
|
||||
worksheet_detections.write(y, 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)
|
||||
worksheet_detections.write(y, 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(y, 6, '\n'.join(detection['location']), wrap_text)
|
||||
worksheet_detections.write(y, 7, detection['comment'][:-1] if detection['comment'].endswith('\n') else detection['comment'], wrap_text)
|
||||
d_comment = get_latest_comment(detection)
|
||||
|
|
@ -463,7 +457,7 @@ def export_techniques_list_to_excel(filename):
|
|||
tmp_date = tmp_date.strftime('%Y-%m-%d')
|
||||
worksheet_visibility.write(y, 4, str(tmp_date).replace('None', ''), valign_top)
|
||||
vs = get_latest_score(visibility)
|
||||
worksheet_visibility.write(y, 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)
|
||||
worksheet_visibility.write(y, 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(y, 6, visibility['comment'][:-1] if visibility['comment'].endswith('\n') else visibility['comment'], wrap_text)
|
||||
worksheet_visibility.write(y, 7, v_comment[:-1] if v_comment.endswith('\n') else v_comment, wrap_text)
|
||||
|
|
|
|||
Loading…
Reference in New Issue