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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
61 lines
1.5 KiB
Python
Executable file
61 lines
1.5 KiB
Python
Executable file
#!/usr/bin/env python2
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# -*-coding:UTF-8 -*
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import redis
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import argparse
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import ConfigParser
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import time
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import os
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from pubsublogger import publisher
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import texttable
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def main():
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"""Main Function"""
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# CONFIG #
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cfg = ConfigParser.ConfigParser()
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cfg.read('./packages/config.cfg')
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# SCRIPT PARSER #
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parser = argparse.ArgumentParser(
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description='''This script is a part of the Assisted Information Leak framework.''',
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epilog='''''')
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parser.add_argument('-db', type=int, default=0,
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help='The name of the Redis DB (default 0)',
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choices=[0, 1, 2, 3, 4], action='store')
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# REDIS #
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r_serv = redis.StrictRedis(
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host=cfg.get("Redis_Queues", "host"),
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port=cfg.getint("Redis_Queues", "port"),
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db=cfg.getint("Redis_Queues", "db"))
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# LOGGING #
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publisher.channel = "Queuing"
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# ZMQ #
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channel = cfg.get("PubSub_Global", "channel")
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# FUNCTIONS #
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publisher.info("""Suscribed to channel {0}""".format(channel))
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while True:
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table = texttable.Texttable()
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table.header(["Queue name", "#Items"])
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row = []
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for queue in r_serv.smembers("queues"):
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current = r_serv.llen(queue)
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current = current - r_serv.llen(queue)
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row.append((queue, r_serv.llen(queue)))
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time.sleep(0.5)
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row.sort()
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table.add_rows(row, header=False)
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os.system('clear')
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print table.draw()
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if __name__ == "__main__":
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main()
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