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https://github.com/ail-project/ail-framework.git
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1379ef705a
AIL is a modular framework to analyse potential information leak from unstructured data source like pastes from Past ebin or similar services. AIL framework is flexible and can be extended to support other functionalities to mine sen sitive information
72 lines
1.8 KiB
Python
Executable file
72 lines
1.8 KiB
Python
Executable file
#!/usr/bin/python2.7
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# -*-coding:UTF-8 -*
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from packages.lib_search import *
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from packages.imported import *
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def main():
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"""Main Function"""
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parser = argparse.ArgumentParser(
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description = 'Analysis Information Leak framework',
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epilog = 'MSc Student Internship')
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parser.add_argument('-db',
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default = 0,
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type = int,
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help = 'The name of the Redis DB',
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choices=[0, 1, 2, 3, 4],
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action = 'store')
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parser.add_argument('name',
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type = str,
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metavar = 'pastename',
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help = 'The name of the paste',
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action = 'store')
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parser.add_argument('-min',
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type = int,
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default = 3,
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help = 'minimum linked hashs (default 3)',
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action = 'store')
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parser.add_argument('-max',
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type = int,
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default = 50,
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help = 'maximum linked hash (execute top.py to be more aware)',
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action = 'store')
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parser.add_argument('-p',
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type = str,
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default = '../graph/Search_',
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metavar = 'path',
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help = "pathname of the file created.",
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action = 'store')
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parser.add_argument('-t',
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type = int,
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default = 0,
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help = 'Type of the Redis population (Same arg than in Populate.py)',
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choices=[0, 2],
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action = 'store')
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args = parser.parse_args()
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r = redis.StrictRedis(
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host='localhost',
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port=6379,
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db=args.db,
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unix_socket_path='/tmp/redis.sock')
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if args.t == 2:
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paste_searching2(r, args.p+args.name+".txt", args.name, args.min, args.max)
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cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
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elif args.t == 0:
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paste_searching(r, args.p+args.name+".txt", args.name, args.min, args.max)
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cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
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pass
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if __name__ == "__main__":
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main()
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