mirror of https://github.com/MISP/misp-galaxy
184 lines
8.0 KiB
Python
Executable File
184 lines
8.0 KiB
Python
Executable File
#!/usr/bin/env python3
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import json
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import re
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import os
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import argparse
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parser = argparse.ArgumentParser(description='Create a couple galaxy/cluster with cti\'s intrusion-sets\nMust be in the mitre/cti/enterprise-attack/intrusion-set folder')
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parser.add_argument("-p", "--path", required=True, help="Path of the mitre/cti folder")
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args = parser.parse_args()
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values = []
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misp_dir = '../../../'
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domains = ['enterprise-attack', 'mobile-attack', 'pre-attack']
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types = ['attack-pattern', 'course-of-action', 'intrusion-set', 'malware', 'tool']
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all_data = {} # variable that will contain everything
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# read in the non-MITRE data
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# we need this to be able to build a list of non-MITRE-UUIDs which we will use later on
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# to remove relations that are from MITRE.
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# the reasoning is that the new MITRE export might contain less relationships than it did before
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# so we cannot migrate all existing relationships as such
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non_mitre_uuids = set()
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for fname in os.listdir(os.path.join(misp_dir, 'clusters')):
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if 'mitre' in fname:
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continue
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if '.json' in fname:
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# print(fname)
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with open(os.path.join(misp_dir, 'clusters', fname)) as f_in:
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cluster_data = json.load(f_in)
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for cluster in cluster_data['values']:
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non_mitre_uuids.add(cluster['uuid'])
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# read in existing MITRE data
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# first build a data set of the MISP Galaxy ATT&CK elements by using the UUID as reference, this speeds up lookups later on.
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# at the end we will convert everything again to separate datasets
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all_data_uuid = {}
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for t in types:
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fname = os.path.join(misp_dir, 'clusters', 'mitre-{}.json'.format(t))
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if os.path.exists(fname):
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# print("##### {}".format(fname))
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with open(fname) as f:
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file_data = json.load(f)
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# print(file_data)
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for value in file_data['values']:
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# remove (old)MITRE relations, and keep non-MITRE relations
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if 'related' in value:
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related_original = value['related']
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related_new = []
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for rel in related_original:
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if rel['dest-uuid'] in non_mitre_uuids:
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related_new.append(rel)
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value['related'] = related_new
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# find and handle duplicate uuids
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if value['uuid'] in all_data_uuid:
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# exit("ERROR: Something is really wrong, we seem to have duplicates.")
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# if it already exists we need to copy over all the data manually to merge it
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# on the other hand, from a manual analysis it looks like it's mostly the relations that are different
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# so now we will just copy over the relationships
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# actually, at time of writing the code below results in no change as the new items always contained more than the previously seen items
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value_orig = all_data_uuid[value['uuid']]
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if 'related' in value_orig:
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for related_item in value_orig['related']:
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if related_item not in value['related']:
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value['related'].append(related_item)
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all_data_uuid[value['uuid']] = value
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# now load the MITRE ATT&CK
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for domain in domains:
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attack_dir = os.path.join(args.path, domain)
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if not os.path.exists(attack_dir):
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exit("ERROR: MITRE ATT&CK folder incorrect")
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with open(os.path.join(attack_dir, domain + '.json')) as f:
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attack_data = json.load(f)
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for item in attack_data['objects']:
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if item['type'] not in types:
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continue
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# print(json.dumps(item, indent=2, sort_keys=True, ensure_ascii=False))
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try:
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# build the new data structure
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value = {}
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uuid = re.search('--(.*)$', item['id']).group(0)[2:]
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# item exist already in the all_data set
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update = False
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if uuid in all_data_uuid:
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value = all_data_uuid[uuid]
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if 'description' in item:
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value['description'] = item['description']
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value['value'] = item['name'] + ' - ' + item['external_references'][0]['external_id']
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value['meta'] = {}
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value['meta']['refs'] = []
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value['uuid'] = re.search('--(.*)$', item['id']).group(0)[2:]
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if 'aliases' in item:
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value['meta']['synonyms'] = item['aliases']
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if 'x_mitre_aliases' in item:
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value['meta']['synonyms'] = item['x_mitre_aliases']
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for reference in item['external_references']:
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if 'url' in reference and reference['url'] not in value['meta']['refs']:
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value['meta']['refs'].append(reference['url'])
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if 'external_id' in reference:
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value['meta']['external_id'] = reference['external_id']
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if 'kill_chain_phases' in item: # many (but not all) attack-patterns have this
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value['meta']['kill_chain'] = []
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for killchain in item['kill_chain_phases']:
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value['meta']['kill_chain'].append(killchain['kill_chain_name'] + ':' + killchain['phase_name'])
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if 'x_mitre_data_sources' in item:
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value['meta']['mitre_data_sources'] = item['x_mitre_data_sources']
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if 'x_mitre_platforms' in item:
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value['meta']['mitre_platforms'] = item['x_mitre_platforms']
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# TODO add the other x_mitre elements dynamically
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# relationships will be build separately afterwards
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value['type'] = item['type'] # remove this before dump to json
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# print(json.dumps(value, sort_keys=True, indent=2))
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all_data_uuid[uuid] = value
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except Exception as e:
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print(json.dumps(item, sort_keys=True, indent=2))
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import traceback
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traceback.print_exc()
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# process the 'relationship' type as we now know the existence of all ATT&CK uuids
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for item in attack_data['objects']:
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if item['type'] != 'relationship':
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continue
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# print(json.dumps(item, indent=2, sort_keys=True, ensure_ascii=False))
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rel_type = item['relationship_type']
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dest_uuid = re.findall(r'--([0-9a-f-]+)', item['target_ref']).pop()
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source_uuid = re.findall(r'--([0-9a-f-]+)', item['source_ref']).pop()
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tags = []
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# add the relation in the defined way
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rel_source = {
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"dest-uuid": dest_uuid,
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"type": rel_type
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}
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if rel_type != 'subtechnique-of':
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rel_source['tags'] = [
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"estimative-language:likelihood-probability=\"almost-certain\""
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]
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if 'related' not in all_data_uuid[source_uuid]:
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all_data_uuid[source_uuid]['related'] = []
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if rel_source not in all_data_uuid[source_uuid]['related']:
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all_data_uuid[source_uuid]['related'].append(rel_source)
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# LATER find the opposite word of "rel_type" and build the relation in the opposite direction
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# dump all_data to their respective file
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for t in types:
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fname = os.path.join(misp_dir, 'clusters', 'mitre-{}.json'.format(t))
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if not os.path.exists(fname):
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exit("File {} does not exist, this is unexpected.".format(fname))
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with open(fname) as f:
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file_data = json.load(f)
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file_data['values'] = []
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for item in all_data_uuid.values():
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# print(json.dumps(item, sort_keys=True, indent=2))
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if 'type' not in item or item['type'] != t: # drop old data or not from the right type
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continue
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item_2 = item.copy()
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item_2.pop('type', None)
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file_data['values'].append(item_2)
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file_data['values'] = sorted(file_data['values'], key=lambda x: sorted(x['value'])) # FIXME the sort algo needs to be further improved
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file_data['version'] += 1
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with open(fname, 'w') as f:
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json.dump(file_data, f, indent=2, sort_keys=True, ensure_ascii=False)
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f.write('\n') # only needed for the beauty and to be compliant with jq_all_the_things
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print("All done, please don't forget to ./validate_all.sh and ./jq_all_the_things.sh")
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