mirror of https://github.com/MISP/misp-galaxy
				
				
				
			
		
			
				
	
	
		
			111 lines
		
	
	
		
			4.0 KiB
		
	
	
	
		
			Python
		
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			4.0 KiB
		
	
	
	
		
			Python
		
	
	
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import argparse
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import csv
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import json
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from collections import defaultdict
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from pathlib import Path
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from uuid import uuid4
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current_path = Path(__file__).resolve().parent
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def _generate_cluster_values(cluster_values: dict):
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    values = []
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    for _, cluster_value in sorted(cluster_values.items()):
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        values.append(cluster_value)
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    return values
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def _parse_csv_input(input_file: Path) -> dict:
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    # We create a mapping to associate the regions and their sub-regions
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    regions_mapping = defaultdict(set)
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    with open(input_file, 'rt', encoding='utf-8') as csvfile:
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        csv_reader = csv.reader(csvfile, delimiter=',')
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        next(csv_reader)
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        for row in csv_reader:
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            '''
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            gc: Global Code
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            gn: Global Name
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            rc: Region Code
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            rn: Region Name
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            src: Sub-region Code
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            srn: Sub-region Name
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            irc: Intermediate Region Code
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            irn: Intermediate Region Name
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            mc: M49 Code
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            coa: Country of Area
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            '''
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            gc, gn, rc, rn, src, srn, irc, irn, mc, coa, *_ = row
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            global_region = f'{gc} - {gn}'
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            if rc and rn:
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                # Almost all the areas have a region information
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                region = f'{rc} - {rn}'
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                regions_mapping[global_region].add(region)
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                # Deal with the region information
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                sub_region = f'{src} - {srn}'
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                regions_mapping[region].add(sub_region)
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                country = f'{mc} - {coa}'
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                if irc and irn:
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                    # If the country is located in an intermediate region
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                    inter_region = f'{irc} - {irn}'
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                    # Deal with the sub-region information
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                    regions_mapping[sub_region].add(inter_region)
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                    # Deal with the intermediate region information
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                    regions_mapping[inter_region].add(country)
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                else:
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                    # The country is located in a sub-region
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                    regions_mapping[sub_region].add(country)
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            else:
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                # Should be only Antarctica which has only global region and
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                # country information
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                country = f'{mc} - {coa}'
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                regions_mapping[global_region].add(country)
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                regions_mapping[country] = None
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    return regions_mapping
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def update_cluster(input_file, filename):
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    with open(filename, 'rt', encoding='utf-8') as f:
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        region_cluster = json.load(f)
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    cluster = {value['value']: value for value in region_cluster['values']}
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    regions_mapping = _parse_csv_input(input_file)
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    is_changed = False
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    for region, subregions in regions_mapping.items():
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        if region not in cluster:
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            cluster_value = {
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                'value': region,
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                'uuid': uuid4().__str__(),
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            }
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            if subregions is not None:
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                cluster_value['meta'] = {
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                    'subregions': sorted(subregions)
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                }
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            cluster[region] = cluster_value
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            is_changed = True
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        else:
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            if subregions != cluster[region].get('meta', {}).get('subregions'):
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                if subregions is not None:
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                    cluster[region]['meta'] = {
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                        'subregions': sorted(subregions)
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                    }
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                is_changed = True
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    if is_changed:
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        region_cluster['values'] = _generate_cluster_values(cluster)
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        with open(filename, 'wt', encoding='utf-8') as f:
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            f.write(json.dumps(region_cluster, indent=2))
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if __name__ == '__main__':
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    parser = argparse.ArgumentParser(description='Generates/updates the region galaxy cluster')
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    parser.add_argument(
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        '-i', '--input', type=Path, default=current_path / 'UNSD.csv',
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        help="CSV input file"
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    )
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    args = parser.parse_args()
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    filename = current_path.parents[1] / 'clusters' / 'region.json'
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    update_cluster(args.input, filename)
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