mirror of https://github.com/MISP/misp-galaxy
102 lines
4.1 KiB
Python
102 lines
4.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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#Used to generate naics galaxy clusters; takes naics.csv as entry
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#naics.csv is extract from [2022]_NAICS_Structure.xlsx and only uses the 2022 NAICS Code and 2022 NAICS Title columns, without title.
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#Note 1 : This only generate the file for the "clusters" folder
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#Note 2 : The generated file needs to pass the jq_all_the_thigs.sh script to be in the corresponding information
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#Note 3 : New uuids are generated on every run
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import json
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import csv
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import uuid
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galaxy={}
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galaxy['description']="The North American Industry Classification System or NAICS is a classification of business establishments by type of economic activity (the process of production)."
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galaxy['name']="NAICS"
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galaxy['source']="North American Industry Classification System - NAICS"
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galaxy['type']="naics"
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galaxy['uuid']="b73ecad4-6529-4625-8c4f-ee3ef703a72a"
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galaxy['version']=2022 #Change when updating
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galaxy['authors']=[]
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galaxy['authors'].append("Executive Office of the President Office of Management and Budget")
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galaxy['category']="sector"
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values = []
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with open('naics.csv', newline='') as csvfile:
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reader = csv.reader(csvfile, delimiter=',', quotechar='"')
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for row in reader:
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#Cluster creation
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cluster = {}
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cluster['value']=row[0]
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cluster['description']=row[1].strip()
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cluster['uuid']=str(uuid.uuid4())
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cluster['related']=[]
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values.append(cluster)
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#Relationsship preparation (Yes it's crappy but at least it works as intended ¯\_(ツ)_/¯)
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relationparent={}
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relationparent['tags']=[]
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relationparent['tags'].append("estimative-language:likelihood-probability=\"likely\"")
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relationparent['type']="parent-of"
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relationchild={}
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relationchild['tags']=[]
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relationchild['tags'].append("estimative-language:likelihood-probability=\"likely\"")
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relationchild['type']="child-of"
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relationsiblings={}
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relationsiblings['tags']=[]
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relationsiblings['tags'].append("estimative-language:likelihood-probability=\"likely\"")
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relationsiblings['type']="similar"
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relationsiblings2={}
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relationsiblings2['tags']=[]
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relationsiblings2['tags'].append("estimative-language:likelihood-probability=\"likely\"")
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relationsiblings2['type']="similar"
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#Building relationships
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if len(cluster['value']) > 2: #2 digit codes have no parents
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if len(cluster['value']) == 6: #specific case of 6 digit codes, parent have only 4 digits
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for value in values:
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if value['value'] == cluster['value'][0:len(cluster['value'])-2]:
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relationchild['dest-uuid']=value['uuid']
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cluster['related'].append(relationchild)
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relationparent['dest-uuid']=cluster['uuid']
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value['related'].append(relationparent)
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break
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if cluster['value'][5] == "0": #If a 6 digit code ends with 0, it has a similar/identical 5 digit code
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for value in values:
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if value['value'] == cluster['value'][0:len(cluster['value'])-1]:
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relationsiblings['dest-uuid']=value['uuid']
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cluster['related'].append(relationsiblings)
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relationsiblings2['dest-uuid']=cluster['uuid']
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value['related'].append(relationsiblings2)
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break
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else: #All other cases (codes with 3 to 5 digits)
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for value in values:
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if value['value'] == cluster['value'][0:len(cluster['value'])-1]:
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relationchild['dest-uuid']=value['uuid']
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cluster['related'].append(relationchild)
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relationparent['dest-uuid']=cluster['uuid']
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value['related'].append(relationparent)
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break
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galaxy['values']=values
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tojson = json.dumps(galaxy, indent=2)
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jsonFile = open("naisc_cluster.json", "w")
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jsonFile.write(tojson)
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jsonFile.close()
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