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Initial import of AIL framework - Analysis Information Leak framework

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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
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Starow 2014-08-06 11:43:40 +02:00
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AIL
===
AIL framework - Analysis Information Leak framework
AIL is a modular framework to analyse potential information leak from unstructured data source like pastes from Pastebin or similar services. AIL framework is flexible and can be extended to support other functionalities to mine sensitive information.
![Dashboard](./doc/screenshots/DashboardAIL.png?raw=true "AIL framework dashboard")
![Trending](./doc/screenshots/WordtrendingAIL.png?raw=true "AIL framework wordtrending")
Requirements & Installation
---------------------------
Obviously:
``sudo apt-get install python2.7``
But also pip, virtualenv and screen.
```
sudo apt-get install python-pip
sudo pip install virtualenv
sudo apt-get install screen
```
You need to create a variable AILENV that will be the installation path:
``export AILENV="/home/user/ail"``
Then create a Python virtual environment:
``virtualenv AILENV``
And install these few more packets:
```
sudo apt-get install g++
sudo apt-get install python-dev
sudo apt-get install python-tk
sudo apt-get install screen
```
Then these modules need to be install with pip inside the virtual environment:
(Activating virtualenv)
```
. ./AILENV/bin/activate
```
You'll need to clone langid:
[https://github.com/saffsd/langid.py]
And install it:
```
python setup.py install
```
That's all the packages you can install with pip:
```
pip install redis
pip install networkx
pip install crcmod
pip install mmh3
pip install dnspython
pip install pyzmq
pip install texttable ----- Queues Monitoring (Optional)
pip install -U textblob
python -m textblob.download_corpora
pip install python-magic
pip install numpy
pip install flask ----- (Optional)
pip install nltk
pip install matplotlib ----- (sudo ln -s freetype2/ft2build.h in /usr/include/)
pip install pybloomfiltermmap ----- (you may need to sudo apt-get install libssl-dev)
```
Installing Redis & Level DB
---------------------------
Assuming that you install everything under /opt/ with adequate permissions:
```
wget http://download.redis.io/releases/redis-2.8.12.tar.gz
tar -xvf redis-2.8.12.tar.gz -C /opt/
```
And follow the README after extraction.
When redis is properly installed you can edit your own config files for
the different required databases or just take the config from the project
located under ``/config/``
```
git clone https://github.com/KDr2/redis-leveldb.git
```
Follow the redis-leveldb README.
Then create these directories
```
cd $AILENV
mkdir PASTES
mkdir Blooms
mkdir dumps
mkdir LEVEL_DB_DATA
cd LEVEL_DB_DATA/
mkdir 2014
mkdir 2013
```
Starting AIL
------------
If you installed all the requirements described above, you should be able to start AIL framework:
```
cd $AILENV
cd bin
./LAUNCH.sh
```
Then you can browse the status of the AIL framework at the following URL:
``http://localhost:7000/``
Create a new module
-------------------
Assuming you already download the project and configure everything:
* Redis databases [http://redis.io/]
* Redis Level DB [https://github.com/KDr2/redis-leveldb]
This module will be recover from a stream all the Tor .onion addresses:
"http://3g2upl4pq6kufc4m.onion/" Which look like this.
Basically we want to match all paste in with ``.onion`` addresses inside.
For that you can already use the module ``ZMQ_PubSub_Categ`` and just
create your own category file in: ``/file/`` here it will be ``/file/onion_categ``.
You need also to link this file inside another file (list_categ_files).
Inside the file "onion_categ", you will add the word "onion" (don't forget the carriage return).
Once it's done, at the launch of the AIL framework, every paste with the word onion inside them
will be forwarded on a specific channel (onion_categ).
Then what you want to do it's recovering these pastes to extract these .onion addresses.
To do that, you'll need to create 2 scripts:
``ZMQ_Sub_Onion_Q.py`` (Redis bufferizing)
``ZMQ_Sub_Onion.py`` (The extraction)
Those two files are there as an example.
Overview
--------
Here is a "chained tree" to show how all ZMQ Modules are linked and how the informations
(mainly the paste) is going through them.
The onion module is interfaced at top down level of this tree (like the ZMQ_Sub_Urls module).
All modules that you want to create using the "tokenization method" and the "categories system" need to be created at this level.
If you want to create a general module (e.g. using all pastes), this module need to be created at the same level than ZMQ_Sub_Duplicate.
![ZMQTree](./doc/dia/ZMQ_Queuing_Tree.jpg?raw=true "ZMQ Tree")
LICENSE
-------
```
Copyright (C) 2014 Jules Debra
Copyright (C) 2014 CIRCL - Computer Incident Response Center Luxembourg (℅ smile gie)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
```

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import argparse
import redis
from bin.pubsublogger import publisher
from bin.packages.lib_words import create_dirfile
import ConfigParser
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read('./packages/config.cfg')
parser = argparse.ArgumentParser(
description='''This script is a part of the Analysis Information Leak
framework. It create a redis list called "listfile" which contain
the absolute filename of all the files from the directory given in
the argument "directory".''',
epilog='Example: ./Dir.py /home/2013/03/')
parser.add_argument('directory', type=str,
help='The directory to run inside', action='store')
parser.add_argument('-db', type=int, default=0,
help='The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4], action='store')
parser.add_argument('-ow', help='trigger the overwritting mode',
action='store_true')
args = parser.parse_args()
r_serv = redis.StrictRedis(host=cfg.get("Redis_Queues", "host"),
port=cfg.getint("Redis_Queues", "port"),
db=cfg.getint("Redis_Queues", "db"))
publisher.channel = "Script"
create_dirfile(r_serv, args.directory, args.ow)
if __name__ == "__main__":
main()

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#!/bin/bash
GREEN="\\033[1;32m"
DEFAULT="\\033[0;39m"
RED="\\033[1;31m"
ROSE="\\033[1;35m"
BLUE="\\033[1;34m"
WHITE="\\033[0;02m"
YELLOW="\\033[1;33m"
CYAN="\\033[1;36m"
#Modify these PATH
export PATH=$(pwd):$PATH
export PATH=/opt/redis-2.8.12/src/:$PATH
export PATH=/opt/redis-leveldb/:$PATH
function helptext {
echo -e $YELLOW"
.o. ooooo ooooo
.888. \`888' \`888'
.8\"888. 888 888
.8' \`888. 888 888
.88ooo8888. 888 888
.8' \`888. 888 888 o
o88o o8888o o o888o o o888ooooood8
Analysis Information Leak framework
"$DEFAULT"
This script launch:
"$CYAN"
- All the ZMQ queuing modules.
- All the ZMQ processing modules.
- All Redis in memory servers.
- All Level-DB on disk servers.
"$DEFAULT"
(Inside screen Daemons)
"$RED"
But first of all you'll need to edit few path where you installed
your redis & leveldb servers.
"$DEFAULT"
Usage:
-----
"
}
function launching_redis {
conf_dir='/home/user/AIL/configs/'
screen -dmS "Redis"
sleep 0.1
echo -e $GREEN"\t* Launching Redis servers"$DEFAULT
screen -S "Redis" -X screen -t "6379" bash -c 'redis-server '$conf_dir'6379.conf ; read x'
sleep 0.1
screen -S "Redis" -X screen -t "6380" bash -c 'redis-server '$conf_dir'6380.conf ; read x'
sleep 0.1
screen -S "Redis" -X screen -t "6381" bash -c 'redis-server '$conf_dir'6381.conf ; read x'
}
function launching_lvldb {
#Want to launch more level_db?
lvdbhost='127.0.0.1'
lvdbdir='/home/user/LEVEL_DB_DATA/'
db1_y='2013'
db2_y='2014'
nb_db=13
screen -dmS "LevelDB"
sleep 0.1
echo -e $GREEN"\t* Launching Levels DB servers"$DEFAULT
#Add lines here with appropriates options.
screen -S "LevelDB" -X screen -t "2013" bash -c 'redis-leveldb -H '$lvdbhost' -D '$lvdbdir'2013/ -P '$db1_y' -M '$nb_db'; read x'
sleep 0.1
screen -S "LevelDB" -X screen -t "2014" bash -c 'redis-leveldb -H '$lvdbhost' -D '$lvdbdir'2014/ -P '$db2_y' -M '$nb_db'; read x'
}
function launching_logs {
screen -dmS "Logging"
sleep 0.1
echo -e $GREEN"\t* Launching logging process"$DEFAULT
screen -S "Logging" -X screen -t "LogQueue" bash -c './log_subscriber -p 6380 -c Queuing -l ../logs/; read x'
sleep 0.1
screen -S "Logging" -X screen -t "LogScript" bash -c './log_subscriber -p 6380 -c Script -l ../logs/; read x'
}
function launching_queues {
screen -dmS "Queue"
sleep 0.1
echo -e $GREEN"\t* Launching redis ZMQ queues"$DEFAULT
screen -S "Queue" -X screen -t "QFeed" bash -c './ZMQ_Feed_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QDuplicate" bash -c './ZMQ_Sub_Duplicate_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QAttributes" bash -c './ZMQ_Sub_Attributes_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "Qlines" bash -c './ZMQ_PubSub_Lines_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QCateg" bash -c './ZMQ_PubSub_Categ_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QTokenize" bash -c './ZMQ_PubSub_Tokenize_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "Qcreditcard" bash -c './ZMQ_Sub_CreditCards_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QOnion" bash -c './ZMQ_Sub_Onion_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "Qmails" bash -c './ZMQ_Sub_Mails_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "Qurls" bash -c './ZMQ_Sub_Urls_Q.py; read x'
sleep 0.1
screen -S "Queue" -X screen -t "QCurve" bash -c './ZMQ_Sub_Curve_Q.py; read x'
}
function launching_scripts {
screen -dmS "Script"
sleep 0.1
echo -e $GREEN"\t* Launching ZMQ scripts"$DEFAULT
screen -S "Script" -X screen -t "Feed" bash -c './ZMQ_Feed.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Duplicate" bash -c './ZMQ_Sub_Duplicate.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Attributes" bash -c './ZMQ_Sub_Attributes.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Lines" bash -c './ZMQ_PubSub_Lines.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Categ" bash -c './ZMQ_PubSub_Categ.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Tokenize" bash -c './ZMQ_PubSub_Tokenize.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Creditcard" bash -c './ZMQ_Sub_CreditCards.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Onion" bash -c './ZMQ_Sub_Onion.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Mails" bash -c './ZMQ_Sub_Mails.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Urls" bash -c './ZMQ_Sub_Urls.py; read x'
sleep 0.1
screen -S "Script" -X screen -t "Curve" bash -c './ZMQ_Sub_Curve.py; read x'
}
#If no params, display the help
#[[ $@ ]] || { helptext; exit 1;}
helptext;
############### TESTS ###################
isredis=`screen -ls | awk '/\.Redis\t/ {print strtonum($1)}'`
islvldb=`screen -ls | awk '/\.LevelDB\t/ {print strtonum($1)}'`
islogged=`screen -ls | awk '/\.Logging\t/ {print strtonum($1)}'`
isqueued=`screen -ls | awk '/\.Queue\t/ {print strtonum($1)}'`
isscripted=`screen -ls | awk '/\.Script\t/ {print strtonum($1)}'`
options=("Redis" "LevelDB" "Logs" "Queues" "Scripts" "Killall" "Shutdown")
menu() {
echo "What do you want to Launch?:"
for i in ${!options[@]}; do
printf "%3d%s) %s\n" $((i+1)) "${choices[i]:- }" "${options[i]}"
done
[[ "$msg" ]] && echo "$msg"; :
}
prompt="Check an option (again to uncheck, ENTER when done): "
while menu && read -rp "$prompt" num && [[ "$num" ]]; do
[[ "$num" != *[![:digit:]]* ]] && (( num > 0 && num <= ${#options[@]} )) || {
msg="Invalid option: $num"; continue
}
((num--)); msg="${options[num]} was ${choices[num]:+un}checked"
[[ "${choices[num]}" ]] && choices[num]="" || choices[num]="+"
done
for i in ${!options[@]}; do
if [[ "${choices[i]}" ]]; then
case ${options[i]} in
Redis)
if [[ ! $isredis ]]; then
launching_redis;
else
echo -e $RED"\t* A screen is already launched"$DEFAULT
fi
;;
LevelDB)
if [[ ! $islvldb ]]; then
launching_lvldb;
else
echo -e $RED"\t* A screen is already launched"$DEFAULT
fi
;;
Logs)
if [[ ! $islogged ]]; then
launching_logs;
else
echo -e $RED"\t* A screen is already launched"$DEFAULT
fi
;;
Queues)
if [[ ! $isqueued ]]; then
launching_queues;
else
echo -e $RED"\t* A screen is already launched"$DEFAULT
fi
;;
Scripts)
if [[ ! $isscripted ]]; then
launching_scripts;
else
echo -e $RED"\t* A screen is already launched"$DEFAULT
fi
;;
Killall)
if [[ $isredis || $islvldb || $islogged || $isqueued || $isscripted ]]; then
kill $isredis $islvldb $islogged $isqueued $isscripted
echo -e $ROSE`screen -ls`$DEFAULT
echo -e $GREEN"\t* $isredis $islvldb $islogged $isqueued $isscripted killed."$DEFAULT
else
echo -e $RED"\t* No screen to kill"$DEFAULT
fi
;;
Shutdown)
bash -c "./Shutdown.py"
;;
esac
fi
done

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

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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
import redis, argparse, zmq, ConfigParser, time, os
from pubsublogger import publisher
from packages import ZMQ_PubSub
import texttable
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read('./packages/config.cfg')
# SCRIPT PARSER #
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework.''',
epilog = '''''')
parser.add_argument('-f',
type = str,
metavar = "filename",
default = "figure",
help = 'The absolute path name of the "figure.png"',
action = 'store')
args = parser.parse_args()
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Level_DB_Hashs", "host"),
port = cfg.getint("Redis_Level_DB_Hashs", "port"),
db = cfg.getint("Redis_Level_DB_Hashs", "db"))
# LOGGING #
publisher.channel = "Graph"
# FUNCTIONS #
publisher.info("""Creating the Repartition Graph""")
total_list = []
codepad_list = []
pastie_list = []
pastebin_list = []
for hash in r_serv.keys():
total_list.append(r_serv.scard(hash))
code = 0
pastie = 0
pastebin = 0
for paste in r_serv.smembers(hash):
source = paste.split("/")[5]
if source == "codepad.org":
code = code + 1
elif source == "pastie.org":
pastie = pastie + 1
elif source == "pastebin.com":
pastebin = pastebin + 1
codepad_list.append(code)
pastie_list.append(pastie)
pastebin_list.append(pastebin)
codepad_list.sort(reverse = True)
pastie_list.sort(reverse = True)
pastebin_list.sort(reverse = True)
total_list.sort(reverse = True)
plt.plot(codepad_list, 'b', label='Codepad.org')
plt.plot(pastebin_list, 'g', label='Pastebin.org')
plt.plot(pastie_list, 'y', label='Pastie.org')
plt.plot(total_list, 'r', label='Total')
plt.xscale('log')
plt.xlabel('Hashs')
plt.ylabel('Occur[Hash]')
plt.title('Repartition')
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(args.f+".png", dpi=None, facecolor='w', edgecolor='b',
orientation='portrait', papertype=None, format="png",
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=True)
if __name__ == "__main__":
main()

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Feed_Q Module
=====================
This module is consuming the Redis-list created by the ZMQ_Feed_Q Module,
And save the paste on disk to allow others modules to work on them.
..todo:: Be able to choose to delete or not the saved paste after processing.
..todo:: Store the empty paste (unprocessed) somewhere in Redis.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances.
*Need the ZMQ_Feed_Q Module running to be able to work properly.
"""
import redis, ConfigParser
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
#REDIS
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
#### SCRIPTS ####
r_serv.sadd("SHUTDOWN_FLAGS", "Feed")
r_serv.sadd("SHUTDOWN_FLAGS", "Categ")
r_serv.sadd("SHUTDOWN_FLAGS", "Lines")
r_serv.sadd("SHUTDOWN_FLAGS", "Tokenize")
r_serv.sadd("SHUTDOWN_FLAGS", "Attributes")
r_serv.sadd("SHUTDOWN_FLAGS", "Creditcards")
r_serv.sadd("SHUTDOWN_FLAGS", "Duplicate")
r_serv.sadd("SHUTDOWN_FLAGS", "Mails")
r_serv.sadd("SHUTDOWN_FLAGS", "Onion")
r_serv.sadd("SHUTDOWN_FLAGS", "Urls")
r_serv.sadd("SHUTDOWN_FLAGS", "Feed_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Categ_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Lines_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Tokenize_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Attributes_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Creditcards_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Duplicate_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Mails_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Onion_Q")
r_serv.sadd("SHUTDOWN_FLAGS", "Urls_Q")
if __name__ == "__main__":
main()

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Feed_Q Module
=====================
This module is consuming the Redis-list created by the ZMQ_Feed_Q Module,
And save the paste on disk to allow others modules to work on them.
..todo:: Be able to choose to delete or not the saved paste after processing.
..todo:: Store the empty paste (unprocessed) somewhere in Redis.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances.
*Need the ZMQ_Feed_Q Module running to be able to work properly.
"""
import redis, zmq, ConfigParser, sys, base64, gzip, os, time
#import zlib
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
#REDIS
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# ZMQ #
channel = cfg.get("Feed", "topicfilter")
#Subscriber
subscriber_name = "feed"
subscriber_config_section = "Feed"
#Publisher
publisher_name = "pubfed"
publisher_config_section = "PubSub_Global"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
PubGlob = ZMQ_PubSub.ZMQPub(configfile, publisher_config_section, publisher_name)
# LOGGING #
publisher.channel = "Script"
publisher.info("Feed Script started to receive & publish.")
while True:
message = Sub.get_msg_from_queue(r_serv)
#Recovering the streamed message informations.
if message != None:
if len(message.split()) == 3:
topic, paste, gzip64encoded = message.split()
print paste
else:
#TODO Store the name of the empty paste inside a Redis-list.
print "Empty Paste: not processed"
publisher.debug("Empty Paste: {0} not processed".format(paste))
continue
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Feed"):
r_serv.srem("SHUTDOWN_FLAGS", "Feed")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
print "Empty Queues: Waiting..."
time.sleep(10)
continue
#Creating the full filepath
filename = cfg.get("Directories", "pastes") + paste
if not os.path.exists(filename.rsplit("/", 1)[0]):
os.makedirs(filename.rsplit("/", 1)[0])
else:
#Path already existing
pass
decoded_gzip = base64.standard_b64decode(gzip64encoded)
#paste, zlib.decompress(decoded_gzip, zlib.MAX_WBITS|16)
with open(filename, 'wb') as F:
F.write(decoded_gzip)
msg = cfg.get("PubSub_Global", "channel")+" "+filename
PubGlob.send_message(msg)
publisher.debug("{0} Published".format(msg))
if __name__ == "__main__":
main()

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bin/ZMQ_Feed_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Feed_Q Module
=====================
This module is the first of the ZMQ tree processing.
It's subscribe to a data stream and put the received messages
into a Redis-list waiting to be popped later by others scripts
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances.
*Messages from the stream should be formated as follow:
"channel_name"+" "+/path/to/the/paste.gz+" "base64_data_encoded_paste"
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
p_serv = r_serv.pipeline(False)
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("Feed", "topicfilter")
Sub = ZMQ_PubSub.ZMQSub(configfile, "Feed", channel, "feed")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Feed_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Feed_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

138
bin/ZMQ_PubSub_Categ.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Categ Module
============================
This module is consuming the Redis-list created by the ZMQ_PubSub_Tokenize_Q Module.
Each words files created under /files/ are representing categories.
This modules take these files and compare them to
the stream of data given by the ZMQ_PubSub_Tokenize_Q Module.
When a word from a paste match one or more of these words file, the filename of
the paste is published/forwarded to the next modules.
Each category (each files) are representing a dynamic channel.
This mean that if you create 1000 files under /files/ you'll have 1000 channels
where every time there is a matching word to a category, the paste containing
this word will be pushed to this specific channel.
..note:: The channel will have the name of the file created.
Implementing modules can start here, create your own category file,
and then create your own module to treat the specific paste matching this category.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (Redis)
*Categories files of words in /files/ need to be created
*Need the ZMQ_PubSub_Tokenize_Q Module running to be able to work properly.
"""
import redis, argparse, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# SCRIPT PARSER #
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework.''',
epilog = '''''')
parser.add_argument('-l',
type = str,
default = "../files/list_categ_files",
help = 'Path to the list_categ_files (../files/list_categ_files)',
action = 'store')
args = parser.parse_args()
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Script"
# ZMQ #
channel = cfg.get("PubSub_Words", "channel_0")
subscriber_name = "categ"
subscriber_config_section = "PubSub_Words"
publisher_name = "pubcateg"
publisher_config_section = "PubSub_Categ"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
Pub = ZMQ_PubSub.ZMQPub(configfile, publisher_config_section, publisher_name)
# FUNCTIONS #
publisher.info("Script Categ subscribed to channel {0}".format(cfg.get("PubSub_Words", "channel_0")))
with open(args.l, 'rb') as L:
tmp_dict = {}
for num, fname in enumerate(L):
#keywords temp list
tmp_list = []
with open(fname[:-1], 'rb') as LS:
for num, kword in enumerate(LS):
tmp_list.append(kword[:-1])
tmp_dict[fname.split('/')[-1][:-1]] = tmp_list
paste_words = []
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
while True:
if message != None:
channel, filename, word, score = message.split()
if prec_filename == None or filename != prec_filename:
PST = P.Paste(filename)
prec_filename = filename
for categ, list in tmp_dict.items():
if word.lower() in list:
channel = categ
msg = channel+" "+PST.p_path+" "+word+" "+score
Pub.send_message(msg)
#dico_categ.add(categ)
publisher.info('{0};{1};{2};{3};{4}'.format("Categ", PST.p_source, PST.p_date, PST.p_name,"Detected "+score+" "+word))
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Categ"):
r_serv.srem("SHUTDOWN_FLAGS", "Categ")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script Categ is Idling 10s")
time.sleep(10)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

61
bin/ZMQ_PubSub_Categ_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Categ_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by others scripts.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_PubSub_Tokenize"
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Words", "channel_0")
subscriber_name = "categ"
subscriber_config_section = "PubSub_Words"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Categ_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Categ_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

128
bin/ZMQ_PubSub_Lines.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Lines Module
============================
This module is consuming the Redis-list created by the ZMQ_PubSub_Line_Q Module.
It perform a sorting on the line's length and publish/forward them to differents
channels:
*Channel 1 if max length(line) < max
*Channel 2 if max length(line) > max
The collected informations about the processed pastes
(number of lines and maximum length line) are stored in Redis.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (LevelDB & Redis)
*Need the ZMQ_PubSub_Line_Q Module running to be able to work properly.
"""
import redis, argparse, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# SCRIPT PARSER #
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework.''',
epilog = '''''')
parser.add_argument('-max',
type = int,
default = 500,
help = 'The limit between "short lines" and "long lines" (500)',
action = 'store')
args = parser.parse_args()
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
p_serv = r_serv.pipeline(False)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
#Subscriber
channel = cfg.get("PubSub_Global", "channel")
subscriber_name = "line"
subscriber_config_section = "PubSub_Global"
#Publisher
publisher_config_section = "PubSub_Longlines"
publisher_name = "publine"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
Pub = ZMQ_PubSub.ZMQPub(configfile, publisher_config_section, publisher_name)
channel_0 = cfg.get("PubSub_Longlines", "channel_0")
channel_1 = cfg.get("PubSub_Longlines", "channel_1")
# FUNCTIONS #
publisher.info("""Lines script Subscribed to channel {0} and Start to publish
on channel {1}, {2}""".format(cfg.get("PubSub_Global", "channel"),
cfg.get("PubSub_Longlines", "channel_0"),
cfg.get("PubSub_Longlines", "channel_1")))
while True:
try:
message = Sub.get_msg_from_queue(r_serv1)
if message != None:
PST = P.Paste(message.split(" ",-1)[-1])
else:
if r_serv1.sismember("SHUTDOWN_FLAGS", "Lines"):
r_serv1.srem("SHUTDOWN_FLAGS", "Lines")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Tokeniser is idling 10s")
time.sleep(10)
continue
lines_infos = PST.get_lines_info()
PST.save_attribute_redis(r_serv, "p_nb_lines", lines_infos[0])
PST.save_attribute_redis(r_serv, "p_max_length_line", lines_infos[1])
r_serv.sadd("Pastes_Objects",PST.p_path)
if lines_infos[1] >= args.max:
msg = channel_0+" "+PST.p_path
else:
msg = channel_1+" "+PST.p_path
Pub.send_message(msg)
except IOError:
print "CRC Checksum Error on : ", PST.p_path
pass
if __name__ == "__main__":
main()

62
bin/ZMQ_PubSub_Lines_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Line_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by others scripts.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_Feed"
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Global", "channel")
subscriber_name = "line"
Sub = ZMQ_PubSub.ZMQSub(configfile,"PubSub_Global", channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Lines_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Lines_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

89
bin/ZMQ_PubSub_Tokenize.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Lines Module
============================
This module is consuming the Redis-list created by the ZMQ_PubSub_Tokenize_Q Module.
It tokenize the content of the paste and publish the result in the following format:
channel_name+' '+/path/of/the/paste.gz+' '+tokenized_word+' '+scoring
..seealso:: Paste method (_get_top_words)
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (Redis)
*Need the ZMQ_PubSub_Tokenize_Q Module running to be able to work properly.
"""
import redis, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Script"
# ZMQ #
channel = cfg.get("PubSub_Longlines", "channel_1")
subscriber_name = "tokenize"
subscriber_config_section = "PubSub_Longlines"
#Publisher
publisher_config_section = "PubSub_Words"
publisher_name = "pubtokenize"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
Pub = ZMQ_PubSub.ZMQPub(configfile, publisher_config_section, publisher_name)
channel_0 = cfg.get("PubSub_Words", "channel_0")
# FUNCTIONS #
publisher.info("Tokeniser subscribed to channel {0}".format(cfg.get("PubSub_Longlines", "channel_1")))
while True:
message = Sub.get_msg_from_queue(r_serv)
print message
if message != None:
PST = P.Paste(message.split(" ",-1)[-1])
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Tokenize"):
r_serv.srem("SHUTDOWN_FLAGS", "Tokenize")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Tokeniser is idling 10s")
time.sleep(10)
print "sleepin"
continue
for word, score in PST._get_top_words().items():
if len(word) >= 4:
msg = channel_0+' '+PST.p_path+' '+str(word)+' '+str(score)
Pub.send_message(msg)
print msg
else:
pass
if __name__ == "__main__":
main()

62
bin/ZMQ_PubSub_Tokenize_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_PubSub_Tokenize_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by others scripts.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_PubSub_Line" channel 1
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Longlines", "channel_1")
subscriber_name = "tokenize"
subscriber_config_section = "PubSub_Longlines"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Tokenize_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Tokenize_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

66
bin/ZMQ_Pub_Global.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Pub_Global Module
=========================
This module is consuming the Redis-list created by the script ./Dir.py.
This module is as the same level of the ZMQ tree than the Module ZMQ_Feed
Whereas the ZMQ_Feed is poping the list created in redis by ZMQ_Feed_Q which is
listening a stream, ZMQ_Pub_Global is poping the list created in redis by ./Dir.py.
Thanks to this Module there is now two way to Feed the ZMQ tree:
*By a continuous stream ..seealso:: ZMQ_Feed Module
*Manually with this module and ./Dir.py script.
Requirements
------------
*Need running Redis instances. (Redis)
"""
import redis, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read('./packages/config.cfg')
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Global"
# ZMQ #
PubGlob = ZMQ_PubSub.ZMQPub(configfile, "PubSub_Global", "global")
# FONCTIONS #
publisher.info("Starting to publish.")
while True:
filename = r_serv.lpop("filelist")
if filename != None:
msg = cfg.get("PubSub_Global", "channel")+" "+filename
PubGlob.send_message(msg)
publisher.debug("{0} Published".format(msg))
else:
time.sleep(10)
publisher.debug("Nothing to publish")
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_Attributes.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Attribute Module
============================
This module is consuming the Redis-list created by the ZMQ_PubSub_Line_Q Module.
It perform a sorting on the line's length and publish/forward them to differents
channels:
*Channel 1 if max length(line) < max
*Channel 2 if max length(line) > max
The collected informations about the processed pastes
(number of lines and maximum length line) are stored in Redis.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (LevelDB & Redis)
*Need the ZMQ_PubSub_Line_Q Module running to be able to work properly.
"""
import redis, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
p_serv = r_serv.pipeline(False)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
#Subscriber
channel = cfg.get("PubSub_Global", "channel")
subscriber_name = "attributes"
subscriber_config_section = "PubSub_Global"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("""ZMQ Attribute is Running""")
while True:
try:
message = Sub.get_msg_from_queue(r_serv1)
if message != None:
PST = P.Paste(message.split(" ",-1)[-1])
else:
if r_serv1.sismember("SHUTDOWN_FLAGS", "Attributes"):
r_serv1.srem("SHUTDOWN_FLAGS", "Attributes")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script Attribute is idling 10s")
time.sleep(10)
continue
encoding = PST._get_p_encoding()
language = PST._get_p_language()
PST.save_attribute_redis(r_serv, "p_encoding", encoding)
PST.save_attribute_redis(r_serv, "p_language", language)
r_serv.sadd("Pastes_Objects",PST.p_path)
PST.save_all_attributes_redis(r_serv)
except IOError:
print "CRC Checksum Failed on :", PST.p_path
publisher.error('{0};{1};{2};{3};{4}'.format("Duplicate", PST.p_source, PST.p_date, PST.p_name, "CRC Checksum Failed" ))
pass
if __name__ == "__main__":
main()

62
bin/ZMQ_Sub_Attributes_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Attributes_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by others scripts.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_Feed"
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Global", "channel")
subscriber_name = "attributes"
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Global", channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Attributes_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Attributes_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

91
bin/ZMQ_Sub_CreditCards.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser, json, pprint, time
from packages import Paste as P
from packages import lib_refine
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
p_serv = r_serv.pipeline(False)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Categ", "creditcard_categ", "cards")
# FUNCTIONS #
publisher.info("Creditcard script subscribed to channel creditcard_categ")
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
creditcard_regex = "4[0-9]{12}(?:[0-9]{3})?"
mastercard_regex = "5[1-5]\d{2}([\ \-]?)\d{4}\1\d{4}\1\d{4}"
visa_regex = "4\d{3}([\ \-]?)\d{4}\1\d{4}\1\d{4}"
discover_regex = "6(?:011\d\d|5\d{4}|4[4-9]\d{3}|22(?:1(?:2[6-9]|[3-9]\d)|[2-8]\d\d|9(?:[01]\d|2[0-5])))\d{10}"
jcb_regex = "35(?:2[89]|[3-8]\d)([\ \-]?)\d{4}\1\d{4}\1\d{4}"
amex_regex = "3[47]\d\d([\ \-]?)\d{6}\1\d{5}"
chinaUP_regex = "62[0-5]\d{13,16}"
maestro_regex = "(?:5[0678]\d\d|6304|6390|67\d\d)\d{8,15}"
while True:
if message != None:
channel, filename, word, score = message.split()
if prec_filename == None or filename != prec_filename:
Creditcard_set = set([])
PST = P.Paste(filename)
for x in PST.get_regex(creditcard_regex):
if lib_refine.is_luhn_valid(x):
Creditcard_set.add(x)
PST.__setattr__(channel, Creditcard_set)
PST.save_attribute_redis(r_serv1, channel, Creditcard_set)
pprint.pprint(Creditcard_set)
if (len(Creditcard_set) > 0):
publisher.warning('{0};{1};{2};{3};{4}'.format("CreditCard", PST.p_source, PST.p_date, PST.p_name, str(len(Creditcard_set))+" Valid number(s)" ))
else:
publisher.info('{0};{1};{2};{3};{4}'.format("CreditCard", PST.p_source, PST.p_date, PST.p_name, "CreditCard Related" ))
prec_filename = filename
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Creditcards"):
r_serv.srem("SHUTDOWN_FLAGS", "Creditcards")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script creditcard is idling 1m")
time.sleep(60)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_CreditCards_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Categ", "creditcard_categ", "cards")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format("creditcard_categ"))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Creditcards_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Creditcards_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_Curve.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Curve Module
============================
This module is consuming the Redis-list created by the ZMQ_PubSub_Tokenize_Q Module.
Each words files created under /files/ are representing categories.
This modules take these files and compare them to
the stream of data given by the ZMQ_PubSub_Tokenize_Q Module.
When a word from a paste match one or more of these words file, the filename of
the paste is published/forwarded to the next modules.
Each category (each files) are representing a dynamic channel.
This mean that if you create 1000 files under /files/ you'll have 1000 channels
where every time there is a matching word to a category, the paste containing
this word will be pushed to this specific channel.
..note:: The channel will have the name of the file created.
Implementing modules can start here, create your own category file,
and then create your own module to treat the specific paste matching this category.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (Redis)
*Categories files of words in /files/ need to be created
*Need the ZMQ_PubSub_Tokenize_Q Module running to be able to work properly.
"""
import redis, argparse, zmq, ConfigParser, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
from packages import lib_words
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# SCRIPT PARSER #
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework.''',
epilog = '''''')
parser.add_argument('-l',
type = str,
default = "../files/list_categ_files",
help = 'Path to the list_categ_files (../files/list_categ_files)',
action = 'store')
args = parser.parse_args()
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Level_DB", "host"),
port = cfg.get("Redis_Level_DB", "port"),
db = 0)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
channel = cfg.get("PubSub_Words", "channel_0")
subscriber_name = "curve"
subscriber_config_section = "PubSub_Words"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("Script Curve subscribed to channel {0}".format(cfg.get("PubSub_Words", "channel_0")))
paste_words = []
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
while True:
if message != None:
channel, filename, word, score = message.split()
if prec_filename == None or filename != prec_filename:
PST = P.Paste(filename)
lib_words.create_curve_with_word_file(r_serv1, "/home/user/AIL/var/www/static/csv/wordstrendingdata", "/home/user/AIL/files/wordfile", int(PST.p_date.year), int(PST.p_date.month))
prec_filename = filename
prev_score = r_serv1.hget(word.lower(), PST.p_date)
print prev_score
if prev_score != None:
r_serv1.hset(word.lower(), PST.p_date, int(prev_score) + int(score))
else:
r_serv1.hset(word.lower(), PST.p_date, score)
#r_serv.expire(word,86400) #1day
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Curve"):
r_serv.srem("SHUTDOWN_FLAGS", "Curve")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script Curve is Idling")
print "sleepin"
time.sleep(1)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

61
bin/ZMQ_Sub_Curve_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Curve_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by others scripts.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_PubSub_Tokenize"
"""
import redis, zmq, ConfigParser
from pubsublogger import publisher
from packages import ZMQ_PubSub
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Words", "channel_0")
subscriber_name = "curve"
subscriber_config_section = "PubSub_Words"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Curve_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Curve_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

196
bin/ZMQ_Sub_Duplicate.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The Duplicate module
====================
This huge module is, in short term, checking duplicates.
Requirements:
-------------
"""
import redis, zmq, ConfigParser, time, datetime, pprint, time, os
from packages import Paste as P
from packages import ZMQ_PubSub
from datetime import date
from pubsublogger import publisher
from pybloomfilter import BloomFilter
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
# DB QUEUE ( MEMORY )
r_Q_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv_merge = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
# REDIS #
# DB OBJECT & HASHS ( DISK )
dico_redis = {}
for year in xrange(2013, 2015):
for month in xrange(0,16):
dico_redis[str(year)+str(month).zfill(2)] = redis.StrictRedis(
host = cfg.get("Redis_Level_DB", "host"),
port = year,
db = month)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
channel = cfg.get("PubSub_Global", "channel")
subscriber_name = "duplicate"
subscriber_config_section = "PubSub_Global"
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, channel, subscriber_name)
# FUNCTIONS #
publisher.info("""Script duplicate subscribed to channel {0}""".format(cfg.get("PubSub_Global", "channel")))
set_limit = 100
while True:
try:
super_dico = {}
hash_dico = {}
dupl = []
nb_hash_current = 0
x = time.time()
message = Sub.get_msg_from_queue(r_Q_serv)
if message != None:
path = message.split(" ",-1)[-1]
PST = P.Paste(path)
else:
publisher.debug("Script Attribute is idling 10s")
time.sleep(10)
if r_Q_serv.sismember("SHUTDOWN_FLAGS", "Duplicate"):
r_Q_serv.srem("SHUTDOWN_FLAGS", "Duplicate")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
continue
PST._set_p_hash_kind("md5")
#Assignate the correct redis connexion
r_serv1 = dico_redis[PST.p_date.year + PST.p_date.month]
#Creating the bloom filter name: bloomyyyymm
bloomname = 'bloom' + PST.p_date.year + PST.p_date.month
bloompath = cfg.get("Directories", "bloomfilters")
filebloompath = bloompath + bloomname
#datetime.date(int(PST.p_date.year),int(PST.p_date.month),int(PST.p_date.day)).timetuple().tm_yday % 7
if os.path.exists(filebloompath):
bloom = BloomFilter.open(filebloompath)
else:
bloom = BloomFilter(100000000, 0.01, filebloompath)
r_Q_serv.sadd("bloomlist", filebloompath)
# UNIQUE INDEX HASHS TABLE
r_serv0 = dico_redis["201300"]
r_serv0.incr("current_index")
index = r_serv0.get("current_index")+str(PST.p_date)
# HASHTABLES PER MONTH (because of r_serv1 changing db)
r_serv1.set(index, PST.p_path)
r_serv1.sadd("INDEX", index)
#For each bloom filter
opened_bloom = []
for bloo in r_Q_serv.smembers("bloomlist"):
#Opening blooms
opened_bloom.append(BloomFilter.open(bloo))
# For each hash of the paste
for hash in PST._get_hash_lines(min = 5, start = 1, jump = 0):
nb_hash_current += 1
#Adding the hash in Redis & limiting the set
if r_serv1.scard(hash) <= set_limit:
r_serv1.sadd(hash, index)
r_serv1.sadd("HASHS", hash)
#Adding the hash in the bloom of the month
bloom.add(hash)
#Go throught the Database of the bloom filter (of the month)
for bloo in opened_bloom:
if hash in bloo:
db = bloo.name[-6:]
#Go throught the Database of the bloom filter (of the month)
r_serv_bloom = dico_redis[db]
#set of index paste: set([1,2,4,65])
hash_current = r_serv_bloom.smembers(hash)
#removing itself from the list
hash_current = hash_current - set([index])
# if the hash is present at least in 1 files (already processed)
if len(hash_current) != 0:
hash_dico[hash] = hash_current
#if there is data in this dictionnary
if len(hash_dico) != 0:
super_dico[index] = hash_dico
else:
# The hash is not in this bloom
pass
###########################################################################################
#if there is data in this dictionnary
if len(super_dico) != 0:
# current = current paste, phash_dico = {hash: set, ...}
occur_dico = {}
for current, phash_dico in super_dico.items():
nb_similar_hash = len(phash_dico)
# phash = hash, pset = set([ pastes ...])
for phash, pset in hash_dico.items():
for p_fname in pset:
occur_dico.setdefault(p_fname, 0)
# Count how much hash is similar per file occuring in the dictionnary
if occur_dico[p_fname] >= 0:
occur_dico[p_fname] = occur_dico[p_fname] + 1
for paste, count in occur_dico.items():
percentage = round((count/float(nb_hash_current))*100, 2)
if percentage >= 50:
dupl.append((paste, percentage))
# Creating the object attribute and save it.
if dupl != []:
PST.__setattr__("p_duplicate", dupl)
PST.save_attribute_redis(r_serv_merge, "p_duplicate", dupl)
y = time.time()
publisher.debug('{0};{1};{2};{3};{4}'.format("Duplicate", PST.p_source, PST.p_date, PST.p_name, "Processed in "+str(y-x)+ " sec" ))
except IOError:
print "CRC Checksum Failed on :", PST.p_path
publisher.error('{0};{1};{2};{3};{4}'.format("Duplicate", PST.p_source, PST.p_date, PST.p_name, "CRC Checksum Failed" ))
pass
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_Duplicate_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
channel = cfg.get("PubSub_Global", "channel")
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Global", channel, "duplicate")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format(channel))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Duplicate_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Duplicate_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

43
bin/ZMQ_Sub_Longlines.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_default", "host"),
port = cfg.getint("Redis_default", "port"),
db = args.db)
p_serv = r_serv.pipeline(False)
# LOGGING #
publisher.channel = "Script"
# ZMQ #
channel = cfg.get("PubSub_Longlines", "channel_0")
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Longlines", channel)
# FUNCTIONS #
publisher.info("Longlines ubscribed to channel {0}".format(cfg.get("PubSub_Longlines", "channel_0")))
while True:
PST = P.Paste(Sub.get_message().split(" ", -1)[-1])
r_serv.sadd("Longlines", PST.p_mime)
PST.save_in_redis(r_serv, PST.p_mime)
if __name__ == "__main__":
main()

82
bin/ZMQ_Sub_Mails.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser, json, pprint, time
from packages import Paste as P
from packages import lib_refine
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
r_serv2 = redis.StrictRedis(
host = cfg.get("Redis_Cache", "host"),
port = cfg.getint("Redis_Cache", "port"),
db = cfg.getint("Redis_Cache", "db"))
# LOGGING #
publisher.channel = "Script"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile,"PubSub_Categ", "mails_categ", "emails")
# FUNCTIONS #
publisher.info("Suscribed to channel mails_categ")
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
email_regex = "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,6}"
while True:
if message != None:
channel, filename, word, score = message.split()
if prec_filename == None or filename != prec_filename:
PST = P.Paste(filename)
MX_values = lib_refine.checking_MX_record(r_serv2, PST.get_regex(email_regex))
if MX_values[0] >= 1:
PST.__setattr__(channel, MX_values)
PST.save_attribute_redis(r_serv1, channel, (MX_values[0], list(MX_values[1])))
pprint.pprint(MX_values)
if MX_values[0] > 10:
publisher.warning('{0};{1};{2};{3};{4}'.format("Mails", PST.p_source, PST.p_date, PST.p_name, str(MX_values[0])+ " e-mails detected" ))
else:
publisher.info('{0};{1};{2};{3};{4}'.format("Mails", PST.p_source, PST.p_date, PST.p_name, str(MX_values[0])+ " e-mails detected" ))
prec_filename = filename
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Mails"):
r_serv.srem("SHUTDOWN_FLAGS", "Mails")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script Mails is Idling 10s")
time.sleep(10)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

42
bin/ZMQ_Sub_Mails_Q.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile,"PubSub_Categ", "mails_categ", "emails")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format("mails_categ"))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Mails_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Mails_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_Onion.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Onion Module
============================
This module is consuming the Redis-list created by the ZMQ_Sub_Onion_Q Module.
It trying to extract url from paste and returning only ones which are tor related
(.onion)
..seealso:: Paste method (get_regex)
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them.
Requirements
------------
*Need running Redis instances. (Redis)
*Need the ZMQ_Sub_Onion_Q Module running to be able to work properly.
"""
import redis, zmq, ConfigParser, json, pprint, time
from packages import Paste as P
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
r_serv2 = redis.StrictRedis(
host = cfg.get("Redis_Cache", "host"),
port = cfg.getint("Redis_Cache", "port"),
db = cfg.getint("Redis_Cache", "db"))
# LOGGING #
publisher.channel = "Script"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Categ", "onion_categ", "tor")
# FUNCTIONS #
publisher.info("Script subscribed to channel onion_categ")
#Getting the first message from redis.
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
#Thanks to Faup project for this regex
# https://github.com/stricaud/faup
url_regex = "([a-zA-Z0-9\.\-]+(\:[a-zA-Z0-9\.&%\$\-]+)*@)*((25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9])\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9]|0)\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9]|0)\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[0-9])|localhost|([a-zA-Z0-9\-]+\.)*[a-zA-Z0-9\-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|onion|[a-zA-Z]{2}))(\:[0-9]+)*(/($|[a-zA-Z0-9\.\,\?\'\\\+&%\$#\=~_\-]+))*"
while True:
if message != None:
channel, filename, word, score = message.split()
# "For each new paste"
if prec_filename == None or filename != prec_filename:
domains_list = []
PST = P.Paste(filename)
for x in PST.get_regex(url_regex):
#Extracting url with regex
credential, subdomain, domain, host, tld, port, resource_path, query_string, f1, f2, f3, f4 = x
if f1 == "onion":
domains_list.append(domain)
#Saving the list of extracted onion domains.
PST.__setattr__(channel, domains_list)
PST.save_attribute_redis(r_serv1, channel, domains_list)
pprint.pprint(domains_list)
print PST.p_path
if len(domains_list) > 0:
publisher.warning('{0};{1};{2};{3};{4}'.format("Onion", PST.p_source, PST.p_date, PST.p_name, str(len(domains_list))+" .onions detected" ))
else:
publisher.info('{0};{1};{2};{3};{4}'.format("Onion", PST.p_source, PST.p_date, PST.p_name, "Onion related" ))
prec_filename = filename
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Onion"):
r_serv.srem("SHUTDOWN_FLAGS", "Onion")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script url is Idling 10s")
time.sleep(10)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
"""
The ZMQ_Sub_Onion_Q Module
============================
This module subscribe to a Publisher stream and put the received messages
into a Redis-list waiting to be popped later by ZMQ_Sub_Onion.
..note:: Module ZMQ_Something_Q and ZMQ_Something are closely bound, always put
the same Subscriber name in both of them (here "tor")
Requirements
------------
*Running Redis instances.
*Should register to the Publisher "ZMQ_PubSub_Categ"
"""
import redis, zmq, ConfigParser
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile,"PubSub_Categ", "onion_categ", "tor")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format("onion_categ"))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Onion_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Onion_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

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bin/ZMQ_Sub_Urls.py Executable file
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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser, json, pprint, time
from packages import Paste as P
from packages import lib_refine
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv1 = redis.StrictRedis(
host = cfg.get("Redis_Data_Merging", "host"),
port = cfg.getint("Redis_Data_Merging", "port"),
db = cfg.getint("Redis_Data_Merging", "db"))
r_serv2 = redis.StrictRedis(
host = cfg.get("Redis_Cache", "host"),
port = cfg.getint("Redis_Cache", "port"),
db = cfg.getint("Redis_Cache", "db"))
# LOGGING #
publisher.channel = "Script"
# ZMQ #
#Subscriber
subscriber_name = "urls"
subscriber_config_section = "PubSub_Categ"
#Publisher
publisher_config_section = "PubSub_Url"
publisher_name = "adress"
pubchannel = cfg.get("PubSub_Url", "channel")
Sub = ZMQ_PubSub.ZMQSub(configfile, subscriber_config_section, "web_categ", subscriber_name)
Pub = ZMQ_PubSub.ZMQPub(configfile, publisher_config_section, publisher_name)
#Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Categ", "web_categ", "urls")
# FUNCTIONS #
publisher.info("Script URL subscribed to channel web_categ")
message = Sub.get_msg_from_queue(r_serv)
prec_filename = None
url_regex = "(http|https|ftp)\://([a-zA-Z0-9\.\-]+(\:[a-zA-Z0-9\.&%\$\-]+)*@)*((25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9])\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9]|0)\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[1-9]|0)\.(25[0-5]|2[0-4][0-9]|[0-1]{1}[0-9]{2}|[1-9]{1}[0-9]{1}|[0-9])|localhost|([a-zA-Z0-9\-]+\.)*[a-zA-Z0-9\-]+\.(com|edu|gov|int|mil|net|org|biz|arpa|info|name|pro|aero|coop|museum|[a-zA-Z]{2}))(\:[0-9]+)*(/($|[a-zA-Z0-9\.\,\?\'\\\+&%\$#\=~_\-]+))*"
while True:
if message != None:
channel, filename, word, score = message.split()
if prec_filename == None or filename != prec_filename:
domains_list = []
PST = P.Paste(filename)
for x in PST.get_regex(url_regex):
scheme, credential, subdomain, domain, host, tld, port, resource_path, query_string, f1, f2, f3, f4 = x
domains_list.append(domain)
msg = pubchannel + " " + str(x)
Pub.send_message(msg)
publisher.debug('{0} Published'.format(x))
if f1 == "onion":
print domain
A_values = lib_refine.checking_A_record(r_serv2, domains_list)
if A_values[0] >= 1:
PST.__setattr__(channel, A_values)
PST.save_attribute_redis(r_serv1, channel, (A_values[0],list(A_values[1])))
pprint.pprint(A_values)
publisher.info('{0};{1};{2};{3};{4}'.format("Url", PST.p_source, PST.p_date, PST.p_name, str(A_values[0])+" Valid url detected" ))
prec_filename = filename
else:
if r_serv.sismember("SHUTDOWN_FLAGS", "Urls"):
r_serv.srem("SHUTDOWN_FLAGS", "Urls")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
publisher.debug("Script url is Idling 10s")
time.sleep(10)
message = Sub.get_msg_from_queue(r_serv)
if __name__ == "__main__":
main()

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, zmq, ConfigParser
from packages import ZMQ_PubSub
from pubsublogger import publisher
configfile = './packages/config.cfg'
def main():
"""Main Function"""
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read(configfile)
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
# LOGGING #
publisher.channel = "Queuing"
# ZMQ #
Sub = ZMQ_PubSub.ZMQSub(configfile, "PubSub_Categ", "web_categ", "urls")
# FUNCTIONS #
publisher.info("""Suscribed to channel {0}""".format("web_categ"))
while True:
Sub.get_and_lpush(r_serv)
if r_serv.sismember("SHUTDOWN_FLAGS", "Urls_Q"):
r_serv.srem("SHUTDOWN_FLAGS", "Urls_Q")
print "Shutdown Flag Up: Terminating"
publisher.warning("Shutdown Flag Up: Terminating.")
break
if __name__ == "__main__":
main()

0
bin/__init__.py Normal file
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bin/log_subscriber Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import argparse
import signal
from pubsublogger import subscriber
def signal_handler(signal, frame):
if subscriber.pubsub is not None:
subscriber.stop()
print "Subscriber closed."
signal.signal(signal.SIGINT, signal_handler)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Configure a logging subscriber.')
parser.add_argument("-H", "--hostname", default='localhost',
type=str, help='Set the hostname of the server.')
parser.add_argument("-p", "--port", default=6379,
type=int, help='Set the server port.')
parser.add_argument('-s', '--use_unix_socket', action='store_true',
help='Use a unix socket path instead of a tcp socket.')
parser.add_argument("--unix_socket_path", default='/tmp/redis.sock',
type=str, help='Unix socket path.')
parser.add_argument("-c", "--channel",
type=str, required=True, help='Channel to subscribe to.')
parser.add_argument("-l", "--log_path",
required=True, help='Path where the logs will be written')
parser.add_argument("-d", "--debug", action="store_true",
help='Also log debug messages.')
parser.add_argument("-m", "--mail", type=file, default=None,
help='Path to the config file used to send errors by email.')
args = parser.parse_args()
if args.use_unix_socket:
subscriber.unix_socket = args.unix_socket_path
else:
subscriber.hostname = args.hostname
subscriber.port = args.port
subscriber.run(args.channel, args.log_path, args.debug, args.mail)

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bin/packages/Date.py Normal file
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class Date(object):
"""docstring for Date"""
def __init__(self, *args):
if len(args) == 3:
self.year = str(args[0])
self.month = str(args[1])
self.day = str(args[2]).zfill(2)
if len(args) == 1:
self.year = str(args[0])[:4]
self.month = str(args[0])[4:6]
self.day = str(args[0])[6:]
def __str__(self):
return "{0}{1}{2}".format(self.year, self.month, self.day)
def _get_year(self):
return self.year
def _get_month(self):
return self.month
def _get_day(self):
return self.day
def _set_year(self, year):
self.year = year
def _set_month(self, month):
self.month = month
def _set_day(self, day):
self.day = day

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bin/packages/Hash.py Normal file
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import hashlib, crcmod, mmh3
class Hash(object):
"""docstring for Hash"""
def __init__(self, name):
self.name = name
def __str__(self):
return "{0}".format(self.name)
def _get_hash_name(self):
return self.name
def _set_hash_name(self, name):
self.p_hash_name = name
def Calculate(self, string):
if self.name == "md5":
hash = hashlib.md5(string).hexdigest()
elif self.name == "sha1":
hash = hashlib.sha1(string).hexdigest()
elif self.name == "crc":
crc32 = crcmod.Crc(0x104c11db7, initCrc=0, xorOut=0xFFFFFFFF)
crc32.update(string)
hash = crc32.hexdigest()
elif self.name == "murmur":
hash = mmh3.hash(string)
return hash

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#!/usr/bin/python2.7
"""
The ``Paste Class``
===================
Use it to create an object from an existing paste or other random file.
Conditions to fulfill to be able to use this class correctly:
-------------------------------------------------------------
1/ The paste need to be saved on disk somewhere (have an accessible path)
2/ The paste need to be gziped.
3/ The filepath need to look like something like this:
/directory/source/year/month/day/paste.gz
"""
import os, magic, gzip, langid, pprint, redis, operator, string, re, json
from Date import Date
from Hash import Hash
from langid.langid import LanguageIdentifier, model
from nltk.tokenize import RegexpTokenizer
from textblob import TextBlob
from lib_refine import *
clean = lambda dirty: ''.join(filter(string.printable.__contains__, dirty))
"""It filters out non-printable characters from the string it receives."""
class Paste(object):
"""
This class representing a Paste as an object.
When created, the object will have by default some "main attributes"
such as the size or the date of the paste already calculated, whereas other
attributes are not set and need to be "asked to be calculated" by their methods.
It was design like this because some attributes take time to be calculated
such as the langage or the duplicate...
:Example:
PST = Paste("/home/2013/ZEeGaez5.gz")
"""
def __init__(self, p_path):
self.p_path = p_path
self.p_name = self.p_path.split('/')[-1]
self.p_size = round(os.path.getsize(self.p_path)/1024.0,2)
self.p_mime = magic.from_buffer(self.get_p_content(), mime = True)
self.p_encoding = None
#Assuming that the paste will alway be in a day folder which is itself
# in a month folder which is itself in a year folder.
# /year/month/day/paste.gz
var = self.p_path.split('/')
self.p_date = Date(var[-4], var[-3], var[-2])
self.p_hash_kind = None
self.p_hash = None
self.p_langage = None
self.p_nb_lines = None
self.p_max_length_line = None
self.p_source = var[-5]
def get_p_content(self):
"""
Returning the content of the Paste
:Example:
PST.get_p_content()
"""
with gzip.open(self.p_path, 'rb') as F:
return F.read()
def get_lines_info(self):
"""
Returning and setting the number of lines and the maximum lenght of the
lines of the paste.
:return: tuple (#lines, max_length_line)
:Example: PST.get_lines_info()
"""
max_length_line = 0
with gzip.open(self.p_path, 'rb') as F:
for nb_line in enumerate(F):
if len(nb_line[1]) >= max_length_line:
max_length_line = len(nb_line[1])
self.p_nb_lines = nb_line[0]
self.p_max_length_line = max_length_line
return (nb_line[0], max_length_line)
def _get_p_encoding(self):
"""
Setting the encoding of the paste.
:Example: PST._set_p_encoding()
"""
try:
return magic.Magic(mime_encoding = True).from_buffer(self.get_p_content())
except magic.MagicException:
pass
def _set_p_hash_kind(self, hashkind):
"""
Setting the hash (as an object) used for futur operation on it.
:Example: PST._set_p_hash_kind("md5")
.. seealso:: Hash.py Object to get the available hashs.
"""
self.p_hash_kind = Hash(hashkind)
def _get_p_hash(self):
"""
Setting the hash of the paste as a kind of "uniq" identificator
:return: hash string (md5, sha1....)
:Example: PST._get_p_hash()
.. note:: You need first to "declare which kind of hash you want to use
before using this function
.. seealso:: _set_p_hash_kind("md5")
"""
self.p_hash = self.p_hash_kind.Calculate(self.get_p_content())
return self.p_hash
def _get_p_language(self):
"""
Returning and setting the language of the paste (guessing)
:Example: PST._get_p_language()
..note:: The language returned is purely guessing and may not be accurate
if the paste doesn't contain any human dictionnary words
..seealso: git@github.com:saffsd/langid.py.git
"""
identifier = LanguageIdentifier.from_modelstring(model, norm_probs=True)
return identifier.classify(self.get_p_content())
def _get_p_hash_kind(self):
return self.p_hash_kind
def _get_p_date(self):
return self.p_date
def _get_hash_lines(self, min = 1, start = 1, jump = 10):
"""
Returning all the lines of the paste hashed.
:param min: -- (int) Minimum line length to be hashed.
:param start: -- (int) Number the line where to start.
:param jump: -- (int) Granularity of the hashing 0 or 1 means no jumps
(Maximum Granularity)
:return: a set([]) of hash.
.. warning:: Using a set here mean that this function will only return uniq hash.
If the paste is composed with 1000 time the same line, this function will return
just once the line.
This choice was made to avoid a certain redundancy and useless hash checking.
:Example: PST._get_hash_lines(1, 1, 0)
.. note:: You need first to "declare which kind of hash you want to use
before using this function
.. seealso:: _set_p_hash_kind("md5")
"""
S = set([])
with gzip.open(self.p_path, 'rb') as F:
for num, line in enumerate(F, start):
if len(line) >= min:
if jump > 1:
if (num % jump) == 1 :
S.add(self.p_hash_kind.Calculate(line))
else:
S.add(self.p_hash_kind.Calculate(line))
return S
def is_duplicate(self, obj, min = 1, percent = 50, start = 1, jump = 10):
"""
Returning the percent of similarity with another paste.
( Using the previous hashing method )
:param obj: (Paste) The paste to compare with
:param min: -- (int) Minimum line length to be hashed.
:param percent: -- (int)
:param start: -- (int) Number the line where to start.
:param jump: -- (int) Granularity of the hashing 0 or 1 means no jumps
(Maximum Granularity)
:return: (tuple) (bool, percent)
:Example:
PST.is_duplicate(PST)
>>> return (True, 100.0)
..seealso: _get_hash_lines()
"""
set1 = self._get_hash_lines(min, start, jump)
set2 = obj._get_hash_lines(min, start, jump)
inter = set.intersection(set1, set2)
numerator = len(inter)
denominator = float((len(set1) + len(set2)) / 2)
try:
var = round((numerator / denominator)*100, 2)
except ZeroDivisionError:
var = 0.0
if var >= percent:
return True, var
else:
return False, var
def save_all_attributes_redis(self, r_serv, key = None):
"""
Saving all the attributes in a "Redis-like" Database (Redis, LevelDB)
:param r_serv: -- Connexion to the Database.
:param key: -- Key of an additionnal set.
Example:
import redis
r_serv = redis.StrictRedis(host = 127.0.0.1, port = 6739, db = 0)
PST = Paste("/home/Zkopkmlk.gz")
PST.save_all_attributes_redis(r_serv)
"""
#LevelDB Compatibility
r_serv.hset(self.p_path, "p_name", self.p_name)
r_serv.hset(self.p_path, "p_size", self.p_size)
r_serv.hset(self.p_path, "p_mime", self.p_mime)
#r_serv.hset(self.p_path, "p_encoding", self.p_encoding)
r_serv.hset(self.p_path, "p_date", self._get_p_date())
r_serv.hset(self.p_path, "p_hash_kind", self._get_p_hash_kind())
r_serv.hset(self.p_path, "p_hash", self.p_hash)
#r_serv.hset(self.p_path, "p_langage", self.p_langage)
#r_serv.hset(self.p_path, "p_nb_lines", self.p_nb_lines)
#r_serv.hset(self.p_path, "p_max_length_line", self.p_max_length_line)
#r_serv.hset(self.p_path, "p_categories", self.p_categories)
r_serv.hset(self.p_path, "p_source", self.p_source)
if key != None:
r_serv.sadd(key, self.p_path)
else:
pass
def save_attribute_redis(self, r_serv, attr_name, value):
"""
Save an attribute as a field
"""
if type(value) == set:
r_serv.hset(self.p_path, attr_name, json.dumps(list(value)))
else:
r_serv.hset(self.p_path, attr_name, json.dumps(value))
def _get_from_redis(self,r_serv):
return r_serv.hgetall(self.p_hash)
def _get_top_words(self, sort = False):
"""
Tokenising method: Returning a sorted list or a set of paste's words
:param sort: Selecting the output: sorted list or a set. (set by default)
:return: set or sorted list of tuple [(word, occurency)...]
:Example: PST._get_top_words(False)
"""
words = {}
tokenizer = RegexpTokenizer('[\&\~\:\;\,\.\(\)\{\}\|\[\]\\\\/\-/\=\'\"\%\$\?\@\+\#\_\^\<\>\!\*\n\r\t\s]+',
gaps = True,
discard_empty = True)
blob = TextBlob(clean(self.get_p_content()),
tokenizer = tokenizer)
for word in blob.tokens:
if word in words.keys():
num = words[word]
else:
num = 0
words[word] = num + 1
if sort:
var = sorted(words.iteritems(), key = operator.itemgetter(1), reverse = True)
else:
var = words
return var
def _get_word(self, word):
"""
Returning a specific word and his occurence if present in the paste
:param word: (str) The word
:return: (tuple) ("foo", 1337)
"""
return [item for item in self._get_top_words() if item[0] == word]
def get_regex(self, regex):
"""
Returning matches with the regex given as an argument.
:param regex: -- (str) a regex
:return: (list)
:Example: PST.get_regex("4[0-9]{12}(?:[0-9]{3})?")
"""
matchs = []
for match in re.findall(regex, self.get_p_content()):
if match != '' and len(match) < 100:
matchs.append(match)
return matchs
if __name__ == "__main__":
pp = pprint.PrettyPrinter(indent=4)
main()

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#!/usr/bin/python2.7
"""
The ``ZMQ PubSub`` Modules
==========================
"""
import zmq, ConfigParser, redis, pprint, os, sys
#from pubsublogger import publisher
class PubSub(object):
"""
The PubSub class is a ``Virtual Class`` which regroup the shared attribute
of a Publisher ZeroMQ and a Subcriber ZeroMQ
:param file_conf: -- (str) The filepath of the configuration file used (.cfg)
:param log_channel: -- (str) The channel used as a log channel
:param ps_name: -- (str) The "ID" of the Publisher/Subcriber
:return: PubSub Object
..note:: The ps_name was implemented to separate subscriber queues in redis
when they are listening on a same "stream"
..seealso:: Method of the ZMQSub class
..todo:: Create Implementing a log channel as an attribute of this virtual class.
"""
def __init__(self, file_conf, log_channel, ps_name):
self._ps_name = ps_name
self._config_parser = ConfigParser.ConfigParser()
self._config_file = file_conf # "./packages/config.cfg"
self._config_parser.read(self._config_file)
self._context_zmq = zmq.Context()
#self._logging_publisher_channel = log_channel # "Default"
#publisher.channel(self._logging_publisher_channel)
class ZMQPub(PubSub):
"""
This class create a ZMQ Publisher which is able to send_message to a choosen socket.
:param pub_config_section: -- (str) The name of the section in the config file to get the settings
:return: ZMQPub Object
:Example:
Extract of the config file:
[PubSub_Categ]
adress = tcp://127.0.0.1:5003
Creating the object and sending message:
MyPublisher = ZMQPub('./packages/config.cfg', 'PubSub_Categ', 'pubcateg')
msg = "categ1"+" "+"Im the data sent on the categ1 channel"
MyPublisher.send_message(msg)
..note:: The ps_name attribute for a publisher is "optionnal" but still required to be
instantiated correctly.
"""
def __init__(self, file_conf, pub_config_section, ps_name):
super(ZMQPub, self).__init__(file_conf, "Default", ps_name)
self._pub_config_section = pub_config_section
self._pubsocket = self._context_zmq.socket(zmq.PUB)
self._pub_adress = self._config_parser.get(self._pub_config_section, "adress")
self._pubsocket.bind(self._config_parser.get(self._pub_config_section, "adress"))
def send_message(self, message):
"""Send a message throught the publisher socket"""
self._pubsocket.send(message)
class ZMQSub(PubSub):
"""
This class create a ZMQ Subcriber which is able to receive message directly or
throught redis as a buffer.
The redis buffer is usefull when the subcriber do a time consuming job which is
desynchronising it from the stream of data received.
The redis buffer ensures that no data will be loss waiting to be processed.
:param sub_config_section: -- (str) The name of the section in the config file to get the settings
:param channel: -- (str) The listening channel of the Subcriber.
:return: ZMQSub Object
:Example:
Extract of the config file:
[PubSub_Global]
adress = tcp://127.0.0.1:5000
channel = filelist
Creating the object and receiving data + pushing to redis (redis buffering):
r_serv = redis.StrictRedis(
host = 127.0.0.1,
port = 6387,
db = 0)
channel = cfg.get("PubSub_Global", "channel")
MySubscriber = ZMQSub('./packages/config.cfg',"PubSub_Global", channel, "duplicate")
while True:
MySubscriber.get_and_lpush(r_serv)
Inside another script use this line to retrive the data from redis.
...
while True:
MySubscriber.get_msg_from_queue(r_serv)
...
..note:: If you don't want any redis buffering simply use the "get_message" method
"""
def __init__(self, file_conf, sub_config_section, channel, ps_name):
super(ZMQSub, self).__init__(file_conf, "Default", ps_name)
self._sub_config_section = sub_config_section
self._subsocket = self._context_zmq.socket(zmq.SUB)
self._sub_adress = self._config_parser.get(self._sub_config_section, "adress")
self._subsocket.connect(self._config_parser.get(self._sub_config_section, "adress"))
self._channel = channel
self._subsocket.setsockopt(zmq.SUBSCRIBE, self._channel)
def get_message(self):
"""
Get the first sent message from a Publisher.
:return: (str) Message from Publisher
"""
return self._subsocket.recv()
def get_and_lpush(self, r_serv):
"""
Get the first sent message from a Publisher and storing it in redis
..note:: This function also create a set named "queue" for monitoring needs
"""
r_serv.sadd("queues",self._channel+self._ps_name)
r_serv.lpush(self._channel+self._ps_name, self._subsocket.recv())
def get_msg_from_queue(self, r_serv):
"""
Get the first sent message from a Redis List
:return: (str) Message from Publisher
"""
return r_serv.rpop(self._channel+self._ps_name)

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[Directories]
bloomfilters = /home/user/Blooms/
pastes = /home/user/PASTES/
##### Redis #####
[Redis_Cache]
host = localhost
port = 6379
db = 0
[Redis_Log]
host = localhost
port = 6380
db = 0
[Redis_Queues]
host = localhost
port = 6381
db = 0
[Redis_Data_Merging]
host = localhost
port = 6379
db = 1
##### LevelDB #####
[Redis_Level_DB]
host = localhost
port = 2013
db = 0
[Redis_Level_DB_Hashs]
host = localhost
port = 2013
db = 1
# PUB / SUB : ZMQ
[Feed]
adress = tcp://crf.circl.lu:5556
topicfilter = 102
[PubSub_Global]
adress = tcp://127.0.0.1:5000
channel = filelist
[PubSub_Longlines]
adress = tcp://127.0.0.1:5001
channel_0 = Longlines
channel_1 = Shortlines
[PubSub_Words]
adress = tcp://127.0.0.1:5002
channel_0 = words
[PubSub_Categ]
adress = tcp://127.0.0.1:5003
#Channels are dynamic (1 channel per categ)
[PubSub_Url]
adress = tcp://127.0.0.1:5004
channel = urls

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[Directories]
bloomfilters = /home/user/Blooms/
pastes = /home/user/PASTES/
##### Redis #####
[Redis_Cache]
host = localhost
port = 6379
db = 0
[Redis_Log]
host = localhost
port = 6380
db = 0
[Redis_Queues]
host = localhost
port = 6381
db = 0
[Redis_Data_Merging]
host = localhost
port = 6379
db = 1
##### LevelDB #####
[Redis_Level_DB]
host = localhost
port = 2013
db = 0
[Redis_Level_DB_Hashs]
host = localhost
port = 2013
db = 1
# PUB / SUB : ZMQ
[Feed]
adress = tcp://crf.circl.lu:5556
topicfilter = 102
[PubSub_Global]
adress = tcp://127.0.0.1:5000
channel = filelist
[PubSub_Longlines]
adress = tcp://127.0.0.1:5001
channel_0 = Longlines
channel_1 = Shortlines
[PubSub_Words]
adress = tcp://127.0.0.1:5002
channel_0 = words
[PubSub_Categ]
adress = tcp://127.0.0.1:5003
#Channels are dynamic (1 channel per categ)
[PubSub_Url]
adress = tcp://127.0.0.1:5004
channel = urls

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import networkx as nx
import xml.sax.saxutils as xlm
import redis
def Gephi_Graph(r_serv, graphpath, mincard, maxcard, insert_type):
"""Create Gephi Graph by calling a "Sub function": Create_Graph
:param r_serv: -- connexion to redis database
:param graphpath: -- the absolute path of the .gephi graph created.
:param mincard: -- the minimum links between 2 nodes to be created
:param maxcard: -- the maximum links between 2 nodes to be created
:param insert_type: -- the type of datastructure used to create the graph.
In fact this function is juste here to be able to choose between two kind of
Redis database structure: One which is a Sorted set and the other a simple
set.
"""
g = nx.Graph()
if (insert_type == 0):
for h in r_serv.smembers("hash"):
Create_Graph(r_serv, g, h, graphpath, mincard, maxcard)
elif (insert_type == 2):
for h in r_serv.zrange("hash", 0, -1):
Create_Graph(r_serv, g, h, graphpath, mincard, maxcard)
nx.write_gexf(g,graphpath)
print nx.info(g)
def Create_Graph(r_serv, graph, h, graphpath, mincard, maxcard):
"""Create Gephi Graph.
:param r_serv: -- connexion to redis database
:param graph: -- networkx graph object
:param h: -- (str) the hash which will be transform into a node.
:param graphpath: -- the absolute path of the .gephi graph created.
:param mincard: -- the minimum links between 2 nodes to be created
:param maxcard: -- the maximum links between 2 nodes to be created
This function link all the pastes with theirs own hashed lines.
Of course a paste can have multiple hashed lines and an hashed line can be
contained in multiple paste.
In this case it's a common hash.
"""
if (r_serv.scard(h) >= mincard) and (r_serv.scard(h) <= maxcard):
for filename in r_serv.smembers(h):
for line in r_serv.smembers(filename):
line = line.decode('UTF-8', errors='ignore')
line = xlm.quoteattr(line, {'"':'&quot;', "'":"&apos;"})
graph.add_edge(h, line+" -- "+filename)
#OK

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import redis, time, sys, os, inspect
from datetime import timedelta, date, datetime
from pubsublogger import publisher
def set_listof_pid(r_serv, filename, name):
"""Create the pid list and it's pid members
:param r_serv: -- Connexion to redis.
:param filename: -- the absolute pastes path name.
:param name: -- the traditionnal argv[0] (The name of the launched script)
This function create a hashes in redis as follows and a set of pid.
+------------+------------+---------------------+
| Keys | Fields | Values |
+============+============+=====================+
| 2045 | startime | 2014-05-09_11:44:17 |
+------------+------------+---------------------+
| ... | prog | ./programme |
+------------+------------+---------------------+
| ... | pid | 2045 |
+------------+------------+---------------------+
| ... | paste | /home/folder/aux.gz |
+------------+------------+---------------------+
| ... | kb | 54.12 |
+------------+------------+---------------------+
+------------+------------+
| Keys | Members |
+============+============+
| pid | 2045 |
+------------+------------+
| ... | 2480 |
+------------+------------+
"""
r_serv.sadd("pid", os.getpid())
r_serv.hmset(os.getpid(),
{
"startime":time.strftime("%Y-%m-%d_%H:%M:%S"),
"prog":name,
"pid":str(os.getpid()),
"paste":filename,
"Kb":round(os.path.getsize(filename)/1024.0,2)
})
def update_listof_pid(r_serv):
"""Remove pid from the pid list
:param r_serv: -- Connexion to redis.
Remove from the list and redis, pid which are terminated.
"""
r_serv.srem("pid", os.getpid())
r_serv.delete(os.getpid())
def flush_list_of_pid(r_serv):
"""Flush the datas in redis
:param r_serv: -- Connexion to redis.
Clean the redis database from the previous pid and pidlist inserted
"""
for x in r_serv.smembers("pid"):
r_serv.delete(x)
r_serv.delete("pid")
def format_display_listof_pid(dico, arg):
"""Formating data for shell and human
:param dico: (dict) dictionnary
:param arg: (str) Choosing argument
:returns: (str)
This function provide different displaying formats for the dictionnary's data.
"""
if arg == 'pid':
var = "{0}".format(dico['pid'])
elif arg == 'up':
var = "{0}".format(dico['uptime'])
elif arg == 'kb':
var = "{0}".format(dico['Kb'])
elif arg == 'paste':
var = "{0}".format(dico['paste'])
elif arg == 'startime':
var = "{0}".format(dico['startime'])
elif arg == 'prg':
var = "{0}".format(dico['prog'])
else:
var = "PID:{0},uptime:{1},kb:{2},paste:{3},prog:{4},startime:{5}".format(dico['pid'],
dico['uptime'],
dico['Kb'],
dico['paste'],
dico['prog'],
dico['startime'])
return var
def display_listof_pid(r_serv, arg):
"""Display the pid list from redis
This function display infos in the shell about lauched process
"""
jobs = {}
joblist = []
try:
for job in r_serv.smembers("pid"):
jobs = r_serv.hgetall(job)
if jobs != None:
start = datetime.strptime(r_serv.hget(job, "startime"), "%Y-%m-%d_%H:%M:%S")
end = datetime.strptime(time.strftime("%Y-%m-%d_%H:%M:%S"), "%Y-%m-%d_%H:%M:%S")
jobs['uptime'] = str(abs(start - end))
joblist.append(jobs)
else:
publisher.debug("display_list_of_pid Aborted due to lack of Information in Redis")
joblist = sorted(joblist, key=lambda k: k['uptime'], reverse=True)
for job in joblist:
print format_display_listof_pid(job, arg)
if arg == "remain":
print "Remaining: {0}".format(r_serv.llen("filelist"))
if arg == "processed":
print "processed: {0}".format(r_serv.llen("processed"))
except TypeError:
publisher.error("TypeError for display_listof_pid")

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import sys, hashlib, os, os.path, gzip, string, glob, itertools, copy, shutil
import redis, crcmod, mmh3, time, fileinput
import crcmod, mmh3
from operator import itemgetter, attrgetter
from pubsublogger import publisher
def listdirectory(path):
"""Path Traversing Function.
:param path: -- The absolute pathname to a directory.
This function is returning all the absolute path of the files contained in
the argument directory.
"""
fichier=[]
for root, dirs, files in os.walk(path):
for i in files:
fichier.append(os.path.join(root, i))
return fichier
clean = lambda dirty: ''.join(filter(string.printable.__contains__, dirty))
"""It filters out non-printable characters from the string it receives."""
def select_hash(hashkind, line):
"""Select the kind of hashing for the line.
:param hashkind: -- (str) The name of the hash
:param line: -- (str) The string to hash.
This function is a kind of hash selector which will use the hash passed
in argument to hash the string also passed in argument.
"""
if hashkind == "md5":
hashline = hashlib.md5(line).hexdigest()
elif hashkind == "sha1":
hashline = hashlib.sha1(line).hexdigest()
elif hashkind == "crc":
crc32 = crcmod.Crc(0x104c11db7, initCrc=0, xorOut=0xFFFFFFFF)
crc32.update(line)
hashline = crc32.hexdigest()
elif hashkind == "murmur":
hashline = mmh3.hash(line)
return str(hashline)
def redis_populate(pipe, folder, minline, hashkind, jmp, insert_type):
"""Call another function with different "mode"
:param pipe: -- Redis pipe
:param folder: -- the absolute path name to the folder where to process
:param minline: -- the minimum lenght of line to hash
:param hashkind: -- the hash to use
:param jmp: -- (bool) trigger the jumping line mode or not
:param insert_type: -- which kind of datastructure to create in redis.
This Function actually call the function "insert_redis" with differents
method to process it.
In one way, x lines are jumped before the Insertion.
In another, all the line are hashed and inserted in redis.
"""
for filename in folder:
with gzip.open(filename, 'rb') as F:
start_line = 1
for num, line in enumerate(F, start_line):
if jmp != 1:
if (num % jmp) == 1 :
insert_redis(filename,
line,
pipe,
minline,
hashkind,
num,
insert_type)
else:
insert_redis(filename,
line,
pipe,
minline,
hashkind,
num,
insert_type)
pipe.execute()
def insert_redis(filename, line, pipe, minline, hashkind, num, insert_type):
"""Insert hashed line in redis.
:param filename: -- the absolute path name to the folder where to process
:param line: -- the clear line which will be hashed.
:param pipe: -- Redis pipe
:param minline: -- the minimum lenght of line to hash
:param hashkind: -- the hash to use
:param num: -- (int) the first line of the file (better human read)
:param insert_type: -- (int) Choose the datastructure used in redis.
This function insert hashed lines in the selected redis datastructure
The datastructure is represented as follow:
case one: ALLIN
"hash"[hashedline][occurence] => to index all different hashs + scoring
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
"L:hashedline"[clearline] => for the correspondance
case two: SORTED SET (for the ./top.py script)
"hash"[hashedline][occurence] => to index all different hashs + scoring
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
case tree: BASIC SET (for ./Graph.py)
"hash"[hashedline] to index all different hashs (without scores)
"hashedline"[filename.gz] => to associate the file.gz to his hashedline
"filename.gz"[firstline] => for human reading
"""
if (insert_type == 2): # ALLIN
if len(line) >= minline:
pipe.zincrby("hash", select_hash(hashkind, line), 1)
pipe.sadd(select_hash(hashkind,line), filename.split('/',20)[-1])
pipe.sadd("L:"+select_hash(hashkind, line), clean(line))
if (num == 1):
pipe.sadd(filename.split('/',20)[-1], clean(line[0:80]))
elif (insert_type == 1): # SORTED SET FOR TOP100.py
if len(line) >= minline:
pipe.zincrby("hash", select_hash(hashkind, line), 1)
pipe.sadd(select_hash(hashkind, line), clean(line))
elif (insert_type == 0): # SET FOR THE GRAPH
if len(line) >= minline:
pipe.sadd("hash", select_hash(hashkind, line))
pipe.sadd(select_hash(hashkind,line), filename.split('/',20)[-1])
if (num == 1):
pipe.sadd(filename.split('/',20)[-1], clean(line[0:80]))
def remove_pure_doppelganger(r_serv, nb):
"""Remove identic paste
:param r_serv: -- Redis connexion database
:param nb: -- (int) Number of execution wanted
Add to a temporary list the hash of wholes files and compare the new hash
to the element of this list. If the hash is already inside, the file
is deleted otherwise the hash is added in the list.
"""
hashlist = []
for x in xrange(0,nb):
filename = r_serv.lpop("filelist")
with open(filename, 'rb') as L:
hashline = hashlib.md5(L.read()).hexdigest()
print len(hashlist)
if hashline in hashlist:
os.remove(filename)
publisher.debug("{0} removed".format(filename))
print "{0} removed".format(filename)
else:
hashlist.append(hashline)

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import gzip, string, sys, os, redis, re
import dns.resolver
from pubsublogger import publisher
from lib_jobs import *
from operator import itemgetter
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
import calendar as cal
from datetime import date, timedelta
from dateutil.rrule import rrule, DAILY
def create_graph_by_day_datastruct(r_serv, r_key, year, month):
"""Creating a datastructure in redis.
:param r_serv: -- Redis connexion database
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
"""
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
r_serv.zadd(r_key+'_by_day',0,dt.strftime("%Y%m%d"))
for Tfilename in r_serv.zrange(r_key+'_occur', 0, -1, withscores = True):
r_serv.zincrby(r_key+'_by_day',
Tfilename[0][-22:-12].replace('/',''),
Tfilename[1])
def is_luhn_valid(card_number):
"""Apply the Luhn algorithm to validate credit card.
:param card_number: -- (int) card number
"""
r = [int(ch) for ch in str(card_number)][::-1]
return (sum(r[0::2]) + sum(sum(divmod(d*2,10)) for d in r[1::2])) % 10 == 0
def checking_MX_record(r_serv, adress_set):
"""Check if emails MX domains are responding.
:param r_serv: -- Redis connexion database
:param adress_set: -- (set) This is a set of emails adress
:return: (int) Number of adress with a responding and valid MX domains
This function will split the email adress and try to resolve their domains
names: on example@gmail.com it will try to resolve gmail.com
"""
score = 0
num = len(adress_set)
WalidMX = set([])
# Transforming the set into a string
MXdomains = re.findall("@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,20}", str(adress_set).lower())
if MXdomains != []:
for MXdomain in set(MXdomains):
try:
#Already in Redis living.
if r_serv.exists(MXdomain[1:]):
score += 1
WalidMX.add(MXdomain[1:])
# Not already in Redis
else:
# If I'm Walid MX domain
if dns.resolver.query(MXdomain[1:], rdtype = dns.rdatatype.MX):
# Gonna be added in redis.
r_serv.setex(MXdomain[1:],timedelta(days=1),1)
score += 1
WalidMX.add(MXdomain[1:])
else:
pass
except dns.resolver.NoNameservers:
publisher.debug('NoNameserver, No non-broken nameservers are available to answer the query.')
except dns.resolver.NoAnswer:
publisher.debug('NoAnswer, The response did not contain an answer to the question.')
except dns.name.EmptyLabel:
publisher.debug('SyntaxError: EmptyLabel')
except dns.resolver.NXDOMAIN:
publisher.debug('The query name does not exist.')
except dns.name.LabelTooLong:
publisher.debug('The Label is too long')
finally:
pass
publisher.debug("emails before: {0} after: {1} (valid)".format(num, score))
return (num, WalidMX)
def checking_A_record(r_serv, domains_set):
score = 0
num = len(domains_set)
WalidA = set([])
for Adomain in domains_set:
try:
#Already in Redis living.
if r_serv.exists(Adomain):
score += 1
WalidA.add(Adomain)
# Not already in Redis
else:
# If I'm Walid domain
if dns.resolver.query(Adomain, rdtype = dns.rdatatype.A):
# Gonna be added in redis.
r_serv.setex(Adomain,timedelta(days=1),1)
score += 1
WalidA.add(Adomain)
else:
pass
except dns.resolver.NoNameservers:
publisher.debug('NoNameserver, No non-broken nameservers are available to answer the query.')
except dns.resolver.NoAnswer:
publisher.debug('NoAnswer, The response did not contain an answer to the question.')
except dns.name.EmptyLabel:
publisher.debug('SyntaxError: EmptyLabel')
except dns.resolver.NXDOMAIN:
publisher.debug('The query name does not exist.')
except dns.name.LabelTooLong:
publisher.debug('The Label is too long')
finally:
pass
publisher.debug("URLs before: {0} after: {1} (valid)".format(num, score))
return (num, WalidA)
def refining_regex_dataset(r_serv, r_key, regex, min_match, year, month, luhn = True, dnscheck = True):
"""Refine the "raw dataset" of paste with regulars expressions
:param r_serv: -- Redis connexion database
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param min_match: -- (int) Below this number file are deleted
:param regex: -- Regular expression which will be match.
This function Refine database created with classify_token_paste function.
It opening again the files which matchs the keywords category list, found
regular expression inside it and count how many time is found.
If there is not too much match about the regular expression the file is
deleted from the list.
Than it finally merge the result by day to be able to create a bar graph
which will represent how many occurence by day the regex match.
"""
for filename in r_serv.zrange(r_key, 0, -1):
with gzip.open(filename, 'rb') as F:
var = 0
matchs = set([])
for num, kword in enumerate(F):
match = re.findall(regex, kword)
var += len(match)
for y in match:
if y != '' and len(y) < 100:
matchs.add(y)
# If there is less match than min_match delete it (False pos)
if len(matchs) <= min_match :
r_serv.zrem(r_key, filename)
publisher.debug("{0} deleted".format(filename))
else:
# else changing the score.
if r_key == "creditcard_categ" and luhn:
for card_number in matchs:
if is_luhn_valid(card_number):
r_serv.zincrby(r_key+'_occur', filename, 1)
publisher.info("{1} is valid in the file {0}".format(filename, card_number))
else:
publisher.debug("{0} card is invalid".format(card_number))
if r_key == "mails_categ" and dnscheck:
r_serv.zadd(r_key+'_occur', checking_MX_record(r_serv, matchs), filename)
else:
# LUHN NOT TRIGGERED (Other Categs)
r_serv.zadd(r_key+'_occur',
len(matchs),
filename)
create_graph_by_day_datastruct(r_serv, r_key, year, month)
def graph_categ_by_day(r_serv, filename, year, month, r_key):
"""Create a bargraph representing regex matching by day
:param r_serv: -- Redis connexion database
:param filename: -- (str) The absolute path where to save the figure.png
:param r_key: -- (str) The name of the key read in redis (often the name of
the keywords category list)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
This function display the amount of the category per day.
"""
adate = []
categ_num = []
rcParams['figure.figsize'] = 15, 10
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
adate.append(dt.strftime("%d"))
categ_num.append(r_serv.zscore(r_key+'_by_day',dt.strftime("%Y%m%d")))
n_groups = len(categ_num)
adress_scores = tuple(categ_num)
index = np.arange(n_groups)
bar_width = 0.5
opacity = 0.6
ladress = plt.bar(index, adress_scores, bar_width,
alpha = opacity,
color = 'b',
label = r_key)
plt.plot(tuple(categ_num), 'r--')
#plt.yscale('log')
plt.xlabel('Days')
plt.ylabel('Amount')
plt.title('Occurence of '+r_key+' by day')
plt.xticks(index + bar_width/2 , tuple(adate))
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(filename+".png", dpi=None, facecolor='w', edgecolor='b',
orientation='portrait', papertype=None, format="png",
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=True)
publisher.info(filename+".png"+" saved!")
def create_tld_list(url = "https://mxr.mozilla.org/mozilla-central/source/netwerk/dns/effective_tld_names.dat?raw=1"):
"""Recover a tld list from url.
:param url: -- The url of the tld list.
:return: -- list
This function recover from mozilla.org the list of the effective tld names,
Save it as a file, and return a list of all the tld.
"""
domains = []
htmlSource = urllib.urlopen(url).read()
with open("ICCANdomain", 'wb') as F:
F.write(htmlSource)
with open("ICCANdomain", 'rb') as F:
for num, line in enumerate(F):
if re.match(r"^\/\/|\n", line) == None:
domains.append(re.sub(r'\*', '', line[:-1]))
else:
publisher.info("Comment line ignored.")
return domains

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import redis
import string
def create_common_hash_file(r_serv, zmin, zmax, filename):
""" Create a "top100".txt file.
:param r_serv: -- connexion to redis database
:param zmin: -- (int) Offset of the top list
:param zmax: -- (int) Number of element wanted to be in the top list.
:param filename: -- the pathname to the created file.
This Function create a ranking list between zmin and zman of the most common
hashs.
Line are written as follow in the file:
hash:[md5hash]:[cardinality]:[line]
All hashes represent a full line which mean it can be one char or more...
"""
with open(filename, 'wb') as F:
for h, num in r_serv.zrevrangebyscore("hash", "+inf", "-inf", zmin, zmax, True):
F.write("hash:{0}:{1}:{2}\n".format(h, num, list(r_serv.smembers('L:'+h))))
def paste_searching(r_serv, filename, pastename, mincard, maxcard):
"""Search similar hashs from a given file.
:param r_serv: -- connexion to redis database
:param filename: -- the pathname to the created file.
:param pastename: -- the name of the paste used to search in redis database.
:param mincard: -- the minimum occurence needed of an hash to be taken in count.
:param maxcard: -- the maximum occurence needed of an hash to be taken in count.
This function return a text file which is a kind of synthesis about
where (in the others pastes) the hash of the given pastename have been found.
"""
P = set([pastename])
tmp_h = str()
tmp_set = set([])
with open(filename, 'wb') as F:
F.write("Paste: {0}\nOptions used:\nMincard: {1}\nMaxcard: {2}\n\nContaining Following Hash:\n".format(pastename,mincard,maxcard))
for h in r_serv.smembers("hash"):
if (r_serv.smembers(h).intersection(P) and r_serv.scard(h) >= mincard and r_serv.scard(h) <= maxcard):
F.write(h+'\n')
tmp_set = tmp_set.union(r_serv.smembers(h).union(r_serv.smembers(tmp_h)))
tmp_h = h
F.write("\nSimilar Files:\n")
for n, s in enumerate(tmp_set):
F.write(str(n) + ': ' + s + '\n')
def paste_searching2(r_serv, filename, pastename, mincard, maxcard):
"""Search similar hashs from a given file.
(On another kind of redis data structure)
:param r_serv: -- connexion to redis database
:param filename: -- the pathname to the created file.
:param pastename: -- the name of the paste used to search in redis database.
:param mincard: -- the minimum occurence needed of an hash to be taken in count.
:param maxcard: -- the maximum occurence needed of an hash to be taken in count.
This function return a text file which is a kind of synthesis about
where (in the others pastes) the hash of the given pastename have been found.
"""
P = set([pastename])
tmp_h = str()
tmp_set = set([])
with open(filename, 'wb') as F:
F.write("Paste: {0}\nOptions used:\nMincard: {1}\nMaxcard: {2}\n\n###Containing Following Hash:### ###Occur### ###### Corresponding Line ######\n".format(pastename,mincard,maxcard))
for h in r_serv.zrange("hash", 0, -1):
if (r_serv.smembers(h).intersection(P) and r_serv.scard(h) >= mincard and r_serv.scard(h) <= maxcard):
F.write(h + ' -- ' + str(r_serv.zscore("hash",h)) + ' -- ' + str(list(r_serv.smembers('L:' + h))) + '\n')
tmp_set = tmp_set.union(r_serv.smembers(h).union(r_serv.smembers(tmp_h)))
tmp_h = h
F.write("\nSimilar Files:\n")
for n, s in enumerate(tmp_set):
F.write(str(n) + ': ' + s + '\n')

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import redis, gzip
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
from textblob import TextBlob
from nltk.corpus import stopwords
from nltk.tokenize import RegexpTokenizer
from lib_redis_insert import clean, listdirectory
from lib_jobs import *
from pubsublogger import publisher
import calendar as cal
from datetime import date, timedelta
from dateutil.rrule import rrule, DAILY
from packages import *
def redis_words_ranking(pipe, r_serv, nb, minlength, maxlength):
"""Looping function
:param pipe: -- Redis pipe.
:param nb: -- (int) Number of pastes proceeded by function
:param minlength: -- (int) passed to the next function
:param maxlength: -- (int) passed to the next function
"""
try:
for n in xrange(0,nb):
path = r_serv.lpop("filelist")
if path != None:
set_listof_pid(r_serv, path, sys.argv[0])
redis_zincr_words(pipe, path, minlength, maxlength)
update_listof_pid(r_serv)
r_serv.lpush("processed",path)
publisher.debug(path)
else:
publisher.debug("Empty list")
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def redis_zincr_words(pipe, filename, minlength, maxlength):
"""Create news sorted set in redis.
:param minlength: -- (int) Minimum words length inserted
:param maxlength: -- (int) Maximum words length inserted
:param filename: -- The absolute path to the file.gz to process.
Representation of the set in redis:
+------------+------------+-----------+
| Keys | Members | Scores |
+============+============+===========+
| 20131001 | word1 | 142 |
+------------+------------+-----------+
| ... | word2 | 120 |
+------------+------------+-----------+
| 20131002 | ... | ... |
+------------+------------+-----------+
This function store all words between minlength and maxlength in redis.
Redis will count as well how much time each word will appear by day:
The cardinality.
"""
tokenizer = RegexpTokenizer('[\&\~\:\;\,\.\(\)\{\}\|\[\]\\\\/\-/\=\'\"\%\$\?\@\+\#\_\^\<\>\!\*\n\r\t\s]+', gaps = True, discard_empty = True)
with gzip.open(filename, 'rb') as F:
blob = TextBlob(clean(F.read()), tokenizer = tokenizer)
for word in blob.tokens:
if (len(word) >= minlength) and (len(word) <= maxlength):
pipe.zincrby(filename[-22:-12].replace('/',''), word, 1)
if (len(word) >= maxlength):
publisher.info("word bigger than {0} detected at {1}".format(maxlength, filename))
publisher.info(word)
pipe.execute()
def classify_token_paste(r_serv, listname, choicedatastruct, nb, r_set):
"""Tokenizing on word category
:param r_serv: -- Redis database connexion
:param listname: -- (str) path to the file containing the list of path of category files
:param choicedatastruct: -- (bool) Changing the index of datastructure
:param nb: -- (int) Number of pastes proceeded by function
Redis data structures cas be choose as follow:
+---------------+------------+-----------+
| Keys | Members | Scores |
+===============+============+===========+
| mails_categ | filename | 25000 |
+---------------+------------+-----------+
| ... | filename2 | 2400 |
+---------------+------------+-----------+
| web_categ | ... | ... |
+---------------+------------+-----------+
Or
+--------------+-------------+-----------+
| Keys | Members | Scores |
+==============+=============+===========+
| filename | mails_categ | 100000 |
+--------------+-------------+-----------+
| ... | web_categ | 24050 |
+--------------+-------------+-----------+
| filename2 | ... | ... |
+--------------+-------------+-----------+
This function tokenise on all special characters like: @^\|[{#~}]!:;$^=
And insert data in redis if the token match the keywords in a list previously
created.
These lists of keywords can be list of everything you want but it's better
to create "category" of keywords.
"""
try:
for n in xrange(0,nb):
filename = r_serv.lpop(r_set)
if filename != None:
tokenizer = RegexpTokenizer('[\&\~\:\;\,\.\(\)\{\}\|\[\]\\\\/\-/\=\'\"\%\$\?\@\+\#\_\^\<\>\!\*\n\r\t\s]+', gaps = True, discard_empty = True)
set_listof_pid(r_serv, filename, sys.argv[0])
with open(listname, 'rb') as L:
# for each "categ" listed in the file
for num, fname in enumerate(L):
# contain keywords by categ
tmp_list = []
#for each keywords
with open(fname[:-1], 'rb') as LS:
for num, kword in enumerate(LS):
tmp_list.append(kword[:-1])
# for each paste
with gzip.open(filename, 'rb') as F:
blob = TextBlob(clean(F.read()),
tokenizer = tokenizer)
# for each paste token
for word in blob.tokens.lower():
if word in tmp_list:
# choosing between two data structures.
if choicedatastruct:
r_serv.zincrby(filename,
fname.split('/')[-1][:-1],
1)
else:
r_serv.zincrby(fname.split('/')[-1][:-1],
filename,
1)
update_listof_pid(r_serv)
else:
publisher.debug("Empty list")
#r_serv.save()
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def dectect_longlines(r_serv, r_key, store = False, maxlength = 500):
"""Store longlines's linenumbers in redis
:param r_serv: -- The redis connexion database
:param r_key: -- (str) The key name in redis
:param store: -- (bool) Store the line numbers or not.
:param maxlength: -- The limit between "short lines" and "long lines"
This function connect to a redis list of filename (pastes filename);
Open the paste and check inside if there is some line with their
length >= to maxlength.
If yes, the paste is "tagged" as containing a longlines in another
redis structures, and the linenumber (of the long lines) can be stored
in addition if the argument store is at True.
"""
try:
while True:
#r_key_list (categ)
filename = r_serv.lpop(r_key)
if filename != None:
set_listof_pid(r_serv, filename, sys.argv[0])
# for each pastes
with gzip.open(filename, 'rb') as F:
var = True
for num, line in enumerate(F):
if len(line) >= maxlength:
#publisher.debug("Longline:{0}".format(line))
if var:
r_serv.rpush("longlines", filename)
var = False
if store:
r_serv.sadd(filename, num)
else:
publisher.debug("Line numbers of longlines not stored")
update_listof_pid(r_serv)
else:
publisher.debug("Empty list")
return False
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
# NOT USED RIGHT NOW #
def recovering_longlines(r_serv):
"""Get longlines with linenumbers
"""
try:
for n in xrange(0,nb):
filename = r_serv.lpop("longlines")
if filename != None:
# For each values in redis (longline's line number)
for numline in r_serv.smembers(filename):
with gzip.open(filename,'rb') as F:
for num, line in enumerate(F):
#When corresponding.
if int(num) == int(numline):
pass
# TREATMENT
else:
publisher.debug("Empty list")
r_serv.save()
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def remove_longline_from_categ(r_serv, r_key, delete, store, maxlength):
"""Remove from a set, file with long lines.
:param r_serv: -- The redis connexion database
:param r_key: -- (str) The key name in redis
:param store: -- (bool) Store the line numbers or not.
:param delete: -- (bool) If true, delete the used key from redis.
:param maxlength: -- The limit between "short lines" and "long lines"
"""
publisher.info("Number of file before:{0}".format(r_serv.zcard(r_key)))
#Create a list of file to proceed (1)
for filename in r_serv.zrange(r_key, 0, -1):
r_serv.rpush(r_key+"_list", filename)
#detecting longlines in pastes
dectect_longlines(r_serv, r_key+"_list", store, maxlength)
#remove false positive members
while True:
fp_filename = r_serv.lpop("longlines")
if fp_filename == None:
break
else:
# if wanted, delete in addition the set with linenumbers (created with store)
if delete:
r_serv.zrem(r_key, fp_filename)
r_serv.delete(fp_filename)
else:
#remove the file with longline from the r_key zset.
r_serv.zrem(r_key, fp_filename)
publisher.info("Longline file removed from {0}, {1} Files remaining".format(r_key, r_serv.zcard(r_key)))
def detect_longline_from_list(r_serv, nb):
try:
for n in xrange(0,nb):
if not dectect_longlines(r_serv, "filelist", True):
break
except (KeyboardInterrupt, SystemExit) as e:
flush_list_of_pid(r_serv)
publisher.debug("Pid list flushed")
def create_dirfile(r_serv, directory, overwrite):
"""Create a file of path.
:param r_serv: -- connexion to redis database
:param directory: -- The folder where to launch the listing of the .gz files
This function create a list in redis with inside the absolute path
of all the pastes needed to be proceeded by function using parallel
(like redis_words_ranking)
"""
if overwrite:
r_serv.delete("filelist")
for x in listdirectory(directory):
r_serv.rpush("filelist",x)
publisher.info("The list was overwritten")
else:
if r_serv.llen("filelist") == 0:
for x in listdirectory(directory):
r_serv.rpush("filelist",x)
publisher.info("New list created")
else:
for x in listdirectory(directory):
r_serv.rpush("filelist",x)
publisher.info("The list was updated with new elements")
def redis_interbargraph_set(r_serv, year, month, overwrite):
"""Create a Redis sorted set.
:param r_serv: -- connexion to redis database
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param overwrite: -- (bool) trigger the overwrite mode
This function create inside redis the intersection of all days in
a month two by two.
Example:
For a month of 31days it will create 30 sorted set between day and
day+1 until the last day.
The overwrite mode delete the intersets and re-create them.
"""
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year, month)[1])
if overwrite:
r_serv.delete("InterSet")
for dt in rrule(DAILY, dtstart = a, until = b - timedelta(1)):
dayafter = dt+timedelta(1)
r_serv.delete(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
r_serv.zinterstore(
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")),
{str(dt.strftime("%Y%m%d")):1,
str(dayafter.strftime("%Y%m%d")):-1})
r_serv.zadd(
"InterSet",
1,
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
else:
for dt in rrule(DAILY, dtstart = a, until = b - timedelta(1)):
dayafter = dt+timedelta(1)
if r_serv.zcard(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d"))) == 0:
r_serv.zinterstore(
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")),
{str(dt.strftime("%Y%m%d")):1,
str(dayafter.strftime("%Y%m%d")):-1})
r_serv.zadd(
"InterSet",
1,
str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d")))
publisher.info(str(dt.strftime("%Y%m%d"))+str(dayafter.strftime("%Y%m%d"))+" Intersection Created")
else:
publisher.warning("Data already exist, operation aborted.")
def word_bar_graph(r_serv, year, month, filename):
"""Create an histogram.
:param r_serv: -- connexion to redis database
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param filename: -- The absolute path where to save the figure.png
This function use matplotlib to create an histogram.
The redis database need obviously to be populated first
with functions: redis_words_ranking and redis_interbargraph_set.
"""
lw = []
adate = []
inter = [0]
rcParams['figure.figsize'] = 15, 10
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year,month)[1])
for dt in rrule(DAILY, dtstart = a, until = b):
lw.append(r_serv.zcard(dt.strftime("%Y%m%d")))
adate.append(dt.strftime("%d"))
for x in r_serv.zrange("InterSet", 0, 31):
inter.append(r_serv.zcard(x))
n_groups = len(lw)
card_words = tuple(lw)
card_interword = tuple(inter)
index = np.arange(n_groups)
bar_width = 0.5
opacity = 0.6
words = plt.bar(index, card_words, bar_width,
alpha=opacity,
color='g',
label='Words/day')
lwords = plt.bar(index - 0.5, card_interword, bar_width,
alpha=opacity,
color='r',
label='Intersection')
plt.plot(tuple(inter), 'b--')
plt.xlabel(str(year)+'/'+str(month)+' Days')
plt.ylabel('Words')
plt.title('Words Cardinality & Intersection Histogram')
plt.xticks(index + bar_width/2 , tuple(adate))
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(filename+".png", dpi=None, facecolor='w', edgecolor='b',
orientation='portrait', papertype=None, format="png",
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=True)
publisher.info(filename+".png"+" saved!")
def create_data_words_curve(r_serv, r_serv2, year, month, filename):
"""Create a Redis hashes.
:param r_serv: -- connexion to redis database (read)
:param r_serv2: -- connexion to redis database (write)
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
:param filename: -- the path to the file which contain a list of words.
The hashes of redis is created as follow:
+------------+------------+-----------+
| Keys | Field | Values |
+============+============+===========+
| word1 | 20131001 | 150 |
+------------+------------+-----------+
| ... | 20131002 | 145 |
+------------+------------+-----------+
| word2 | ... | ... |
+------------+------------+-----------+
The filename need to be a list of words separated by a carriage return
with an empty line at the end.
This function create datas which is used by the function
create_curve_with_word_file which create a csv file.
"""
stop = stopwords.words('english')
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year,month)[1])
with open(filename, 'rb') as F:
for line in F:
for dt in rrule(DAILY, dtstart = a, until = b):
if r_serv.zscore(dt.strftime("%Y%m%d"), line[:-1]) is not None:
#tester si ca existe deja "en option" et ajouter un WARNING log
r_serv2.hmset(line[:-1], {str(dt.strftime("%Y%m%d")):r_serv.zscore(dt.strftime("%Y%m%d"), line[:-1])})
else:
pass
def create_curve_with_word_file(r_serv, csvfilename, feederfilename, year, month):
"""Create a csv file used with dygraph.
:param r_serv: -- connexion to redis database
:param csvfilename: -- the path to the .csv file created
:param feederfilename: -- the path to the file which contain a list of words.
:param year: -- (integer) The year to process
:param month: -- (integer) The month to process
This function create a .csv file using datas in redis.
It's checking if the words contained in feederfilename and
their respectives values by days exists. If these values are missing
(Word not present during a day) it's will automatically put a 0
to keep the timeline of the curve correct.
"""
a = date(year, month, 01)
b = date(year, month, cal.monthrange(year,month)[1])
days = {}
words = []
with open(feederfilename, 'rb') as F:
for word in F: # words of the files
words.append(word[:-1]) # list of words (sorted as in the file)
for dt in rrule(DAILY, dtstart = a, until = b): # for each days
mot = []
mot1 = []
mot2 = []
days[dt.strftime("%Y%m%d")] = ''
for word in sorted(words): # from the 1srt day to the last of the list
if r_serv.hexists(word, dt.strftime("%Y%m%d")): # if the word have a value for the day
mot1.append(str(word))
mot2.append(r_serv.hget(word, dt.strftime("%Y%m%d")))
mot = zip(mot1, mot2)
days[dt.strftime("%Y%m%d")] = mot
else:
mot1.append(str(word))
mot2.append(0)
mot = zip(mot1, mot2)
days[dt.strftime("%Y%m%d")] = mot
with open(csvfilename+".csv", 'wb') as F:
F.write("Date," + ",".join(sorted(words)) + '\n')
for x, s in days.items():
val = []
for y in s:
val.append(y[1])
F.write(x + ',' + str(val) + '\n')
with open(csvfilename+".csv", 'rb') as F:
h = F.read()
h = h.replace("[","")
h = h.replace("]","")
h = h.replace('\'',"")
with open(csvfilename+".csv", 'wb') as F:
F.write(h)

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#!/usr/bin/python
# -*- coding: utf-8 -*-
"Core exceptions raised by the PubSub module"
class PubSubError(Exception):
pass
class InvalidErrorLevel(PubSubError):
pass
class NoChannelError(PubSubError):
pass

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#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
:mod:`publisher` -- Publish logging messages on a redis channel
To use this module, you have to define at least a channel name.
.. note::
The channel name should represent the area of the program you want
to log. It can be whatever you want.
"""
import redis
from pubsublogger.exceptions import InvalidErrorLevel, NoChannelError
# use a TCP Socket by default
use_tcp_socket = True
#default config for a UNIX socket
unix_socket = '/tmp/redis.sock'
# default config for a TCP socket
hostname = 'localhost'
port = 6380
channel = None
redis_instance = None
__error_levels = ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL')
def __connect():
"""
Connect to a redis instance.
"""
global redis_instance
if use_tcp_socket:
redis_instance = redis.StrictRedis(host=hostname, port=port)
else:
redis_instance = redis.StrictRedis(unix_socket_path = unix_socket)
def log(level, message):
"""
Publish `message` with the `level` the redis `channel`.
:param level: the level of the message
:param message: the message you want to log
"""
if redis_instance is None:
__connect()
if level not in __error_levels:
raise InvalidErrorLevel('You have used an invalid error level. \
Please choose in: ' + ', '.join(__error_levels))
if channel is None:
raise NoChannelError('Please set a channel.')
c = '{channel}.{level}'.format(channel=channel, level=level)
redis_instance.publish(c, message)
def debug(message):
"""
Publush a DEBUG `message`
"""
log('DEBUG', message)
def info(message):
"""
Publush an INFO `message`
"""
log('INFO', message)
def warning(message):
"""
Publush a WARNING `message`
"""
log('WARNING', message)
def error(message):
"""
Publush an ERROR `message`
"""
log('ERROR', message)
def critical(message):
"""
Publush a CRITICAL `message`
"""
log('CRITICAL', message)

140
bin/pubsublogger/subscriber.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
:mod:`subscriber` -- Subscribe to a redis channel and gather logging messages.
To use this module, you have to define at least a channel name.
"""
import redis
from logbook import Logger
import ConfigParser
from logbook import NestedSetup, NullHandler, FileHandler, MailHandler
import os
# use a TCP Socket by default
use_tcp_socket = True
#default config for a UNIX socket
unix_socket = '/tmp/redis.sock'
# default config for a TCP socket
hostname = 'localhost'
port = 6379
pubsub = None
channel = None
# Required only if you want to send emails
dest_mails = []
smtp_server = None
smtp_port = 0
src_server = None
def setup(name, path = 'log', enable_debug = False):
"""
Prepare a NestedSetup.
:param name: the channel name
:param path: the path where the logs will be written
:param enable_debug: do we want to save the message at the DEBUG level
:return a nested Setup
"""
path_tmpl = os.path.join(path, '{name}_{level}.log')
info = path_tmpl.format(name = name, level = 'info')
warn = path_tmpl.format(name = name, level = 'warn')
err = path_tmpl.format(name = name, level = 'err')
crit = path_tmpl.format(name = name, level = 'crit')
# a nested handler setup can be used to configure more complex setups
setup = [
# make sure we never bubble up to the stderr handler
# if we run out of setup handling
NullHandler(),
# then write messages that are at least info to to a logfile
FileHandler(info, level='INFO', encoding='utf-8'),
# then write messages that are at least warnings to to a logfile
FileHandler(warn, level='WARNING', encoding='utf-8'),
# then write messages that are at least errors to to a logfile
FileHandler(err, level='ERROR', encoding='utf-8'),
# then write messages that are at least critical errors to to a logfile
FileHandler(crit, level='CRITICAL', encoding='utf-8'),
]
if enable_debug:
debug = path_tmpl.format(name = name, level = 'debug')
setup.insert(1, FileHandler(debug, level='DEBUG', encoding='utf-8'))
if src_server is not None and smtp_server is not None \
and smtp_port != 0 and len(dest_mails) != 0:
mail_tmpl = '{name}_error@{src}'
from_mail = mail_tmpl.format(name = name, src = src_server)
subject = 'Error in {}'.format(name)
# errors should then be delivered by mail and also be kept
# in the application log, so we let them bubble up.
setup.append(MailHandler(from_mail, dest_mails, subject,
level='ERROR', bubble=True, server_addr=(smtp_server, smtp_port)))
return NestedSetup(setup)
def mail_setup(path):
"""
Set the variables to be able to send emails.
:param path: path to the config file
"""
global dest_mails
global smtp_server
global smtp_port
global src_server
config = ConfigParser.RawConfigParser()
config.readfp(path)
dest_mails = config.get('mail', 'dest_mail').split(',')
smtp_server = config.get('mail', 'smtp_server')
smtp_port = config.get('mail', 'smtp_port')
src_server = config.get('mail', 'src_server')
def run(log_name, path, debug = False, mail = None):
"""
Run a subscriber and pass the messages to the logbook setup.
Stays alive as long as the pubsub instance listen to something.
:param log_name: the channel to listen to
:param path: the path where the log files will be written
:param debug: True if you want to save the debug messages too
:param mail: Path to the config file for the mails
"""
global pubsub
global channel
channel = log_name
if use_tcp_socket:
r = redis.StrictRedis(host=hostname, port=port)
else:
r = redis.StrictRedis(unix_socket_path = unix_socket)
pubsub = r.pubsub()
pubsub.psubscribe(channel + '.*')
logger = Logger(channel)
if mail is not None:
mail_setup(mail)
if os.path.exists(path) and not os.path.isdir(path):
raise Exception("The path you want to use to save the file is invalid (not a directory).")
if not os.path.exists(path):
os.mkdir(path)
with setup(channel, path, debug):
for msg in pubsub.listen():
if msg['type'] == 'pmessage':
level = msg['channel'].split('.')[1]
message = msg['data']
try:
message = message.decode('utf-8')
except:
pass
logger.log(level, message)
def stop():
"""
Unsubscribe to the channel, stop the script.
"""
pubsub.punsubscribe(channel + '.*')

56
bin/tests/Bargraph.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create an histogram which display the occurency
of the words per day but also the intersection of day and day-1 of these
occurencies''',
epilog = '''The Redis database need to be populated by the script
Wordsranking_Populate.py before using this one.''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed.',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed.',
action = 'store')
parser.add_argument('-f',
type = str,
metavar = "filename",
default = "figure",
help = 'The absolute path name of the "figure.png"',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
word_bar_graph(r,args.y,args.m, args.f)
if __name__ == "__main__":
main()

64
bin/tests/Bargraph_categ_by_day.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_refine import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create an histogram which display the occurency
of the word category per days.''',
epilog = '''The Redis database need to be populated by the script
Classify_Paste_Token.py before.
It's also usefull to launch Remove_longline_fp.py and Refine_with_regex.py
to create a more accurate histogram.
example: ./Bargraph_categ_by_day.py 2013 12 mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-f',
type = str,
metavar = "filename",
default = "figure",
help = 'The absolute path name of the "figure.png"',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed',
action = 'store')
parser.add_argument('key',
type = str,
help ='name of the key to process in redis (the word_categ concerned)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
graph_categ_by_day(r, args.f, args.y, args.m, args.key)
if __name__ == "__main__":
main()

61
bin/tests/Classify_Paste_Token.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create sets in redis as much as category
defined in the file given by the argument -l ''',
epilog = '''Example : seq 5000 | parallel -n0 -j 10
./classify_Paste_Token.py -nbp 200''')
parser.add_argument('-l',
type = str,
default = "../files/list_categ_files",
help = 'Path to the list_categ_files (../files/list_categ_files)',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-s',
help = 'Datastruct type, swapping between keys & members',
action = 'store_true')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'Nbpaste',
action = 'store')
parser.add_argument('-set',
type = str,
default = 'filelist',
help = 'The name of the list in redis which contain the filename to tokenise',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
classify_token_paste(r, args.l, args.s, args.nbp, args.set)
if __name__ == "__main__":
main()

46
bin/tests/Display_pid.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It's here to monitor some script which take time
and lauched in parallel, You can display which process is running on which
paste and how much time it spent processing it''',
epilog = 'example : ./Display_pid -p pid -db 1 -d remain')
parser.add_argument('-d',
type = str,
default = 'all',
choices=['paste', 'up', 'start', 'kb', 'all', 'pid', 'prg', 'remain', 'processed'],
help = 'Which info to display ?',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
display_listof_pid(r, args.d)
if __name__ == "__main__":
main()

65
bin/tests/Graph.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_gephi import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It create a gephi graph to have a global
view of the pastes but also which one are similar.''',
epilog = '''The Redis database need to be populated by the script
Populate.py before using this one.''')
parser.add_argument('-t',
type = int,
default = 0,
help = 'Type of the Redis population (Same arg than in Populate.py)',
choices=[0, 2],
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-min',
type = int,
default = 3,
help = 'minimum linked nodes (default 3)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 50,
help = 'maximum linked nodes created (execute top.py before for more info)',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/out',
metavar = 'path',
help = "pathname of the graph file created. ex: /home/graph",
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db,
unix_socket_path='/tmp/redis.sock')
Gephi_Graph(r, args.p+".gexf", args.min, args.max, args.t)
cprint("GRAPH CREATED AT:{0}.gexf".format(args.p),"green")
if __name__ == "__main__":
main()
#OK

52
bin/tests/Interset.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It create in redis the intersection
between all the days two by two of the date given in argument.''',
epilog = '''The Redis database need to be populated by the script
Wordsranking_Populate.py before using this one.''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
parser.add_argument('-ow',
help = 'trigger the overwritting mode',
action = 'store_true')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
redis_interbargraph_set(r, args.y, args.m, args.ow)
if __name__ == "__main__":
main()

75
bin/tests/Populate.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_redis_insert import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. Is Populate the Redis database with
the pastes names and theirs hashed line''',
epilog = '''This script need to be run first in order to use the others:
Graph.py, Search.py, Top.py ...''')
parser.add_argument('input',
type = str,
metavar = 'pathfolder',
help = 'Input folder',
action = 'store')
parser.add_argument('-t',
type = int,
default = 0,
help = 'type of population wanted 0 = set 1 = zset 2 = mix',
choices=[0, 1, 2],
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-H',
type = str,
default = 'md5',
metavar='hash',
help = 'The hash method (default md5)',
choices=["md5", "sha1", "crc", "murmur"],
action = 'store')
parser.add_argument('-jmp',
type = int,
default = 10,
metavar = 'jump',
help = '''Jumping line factor. 1 = All the line are taken. X = jump X line
(default 10)''',
action = 'store')
parser.add_argument('-ml',
type = int,
default = 1,
metavar = 'minlnline',
help = '''Length line factor. 1 = All the line are taken.
X = each line >= X char (default 1)''',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline()
redis_populate(p, listdirectory(args.input), args.ml, args.H, args.jmp, args.t)
if __name__ == "__main__":
main()
#OK

78
bin/tests/Refine_with_regex.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_refine import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. Is refining a redis set by
re analysing set with regex and changing the score by the number of
regex matching''',
epilog = '''example of use: ./Refine_with_regex.py 2013 12 -regex mail
-key mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-nbm',
type = int,
default = 1,
help = 'Minimum matching regex occurence per file to keep in redis (1)',
action = 'store')
parser.add_argument('-regex',
type = str,
default = 'mail',
choices=['mail', 'card', 'url', 'bitcoin'],
help = 'Which regex wanted to be use to match',
action = 'store')
parser.add_argument('-key',
type = str,
default = "mails_categ",
help = 'Name of the key to process in redis (same name than the wordlist concerned)',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year processed',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month processed',
action = 'store')
args = parser.parse_args()
if args.regex == 'mail':
regex = "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,6}"
elif args.regex == 'card':
regex = "4[0-9]{12}(?:[0-9]{3})?"
elif args.regex == 'bitcoin':
regex = "[13][1-9A-HJ-NP-Za-km-z]{26,33}"
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
refining_regex_dataset(r, args.key, regex, args.nbm, args.y, args.m)
if __name__ == "__main__":
main()

44
bin/tests/Remove_Doppelganger.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_redis_insert import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information
Leak framework. It Add to a temporary list the hash
of wholes files and compare the new hash to the element of this
list. If the hash is already inside, the file is deleted
otherwise the hash is added in the list.''',
epilog = '''This script need Redis to be populated before by
./Dir.py''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'nbpaste',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
remove_pure_doppelganger(r, args.nbp)
if __name__ == "__main__":
main()

57
bin/tests/Remove_longline_fp.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It removes the line which are in redis under
the "key" name argument''',
epilog = '''This script is usually usefull launched after using
./Classify_Paste_Token.py example: ./Remove_longline_fp.py mails_categ''')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('key',
type = str,
help = 'Name of the key to process in redis ("")',
action = 'store')
parser.add_argument('-d',
help = 'Delete the set of longline created?',
action = 'store_true')
parser.add_argument('-s',
help = 'Store the longline numbers inside a set?',
action = 'store_true')
parser.add_argument('-max',
type = int,
default = 500,
help = 'The limit between "short lines" and "long lines" (500)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
#remove_longline_from_categ(r, args.key, args.d, args.s, args.max)
detect_longline_from_list(r,args.max)
if __name__ == "__main__":
main()

72
bin/tests/Search.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_search import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'MSc Student Internship')
parser.add_argument('-db',
default = 0,
type = int,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('name',
type = str,
metavar = 'pastename',
help = 'The name of the paste',
action = 'store')
parser.add_argument('-min',
type = int,
default = 3,
help = 'minimum linked hashs (default 3)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 50,
help = 'maximum linked hash (execute top.py to be more aware)',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/Search_',
metavar = 'path',
help = "pathname of the file created.",
action = 'store')
parser.add_argument('-t',
type = int,
default = 0,
help = 'Type of the Redis population (Same arg than in Populate.py)',
choices=[0, 2],
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db,
unix_socket_path='/tmp/redis.sock')
if args.t == 2:
paste_searching2(r, args.p+args.name+".txt", args.name, args.min, args.max)
cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
elif args.t == 0:
paste_searching(r, args.p+args.name+".txt", args.name, args.min, args.max)
cprint("GRAPH CREATED AT:{0}{1}.txt".format(args.p,args.name),"green")
pass
if __name__ == "__main__":
main()

58
bin/tests/Top.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_search import Create_Common_Hash_File
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = '''This script is a part of the Analysis Information Leak
framework. It create a text file with the top common hash
which are in the redis database''',
epilog = '''The Redis database need to be populated by the script
Populate.py before using this one.''')
parser.add_argument('-db',
default = 0,
type = int,
help = 'The name of the Redis DB',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-off',
default = 1,
type = int,
metavar = 'offset',
help = 'Starting point of the toplist',
action = 'store')
parser.add_argument('-top',
default = 100,
type = int,
metavar = '100',
help = 'How many occurence? top 10-50-100 ?',
action = 'store')
parser.add_argument('-p',
type = str,
default = '../graph/top',
metavar = 'path',
help = "pathname of the file created ex: /home/top",
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
create_common_cash_file(r, args.off, args.top, args.p+str(args.top)+".top")
cprint("LIST CREATED","green")
if __name__ == "__main__":
main()
#OK

64
bin/tests/WordsCurve_Populate.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'Thats drawing')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB To get the info (0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-db1',
type = int,
default = 1,
help = 'The name of the Redis DB To store (1)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('f',
type = str,
metavar= "file",
help = 'Words filename',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
r2 = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db1)
p = r.pipeline(False)
create_data_words_curve(r, r2, args.y, args.m, args.f)
if __name__ == "__main__":
main()

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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'Thats drawing')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-cvs',
type = str,
metavar = "filename",
default = "wordstrendingdata",
help = 'The name of the cvs file wanted to be created',
action = 'store')
parser.add_argument('f',
type = str,
help = 'The file with the list of words',
action = 'store')
parser.add_argument('y',
type = int,
metavar = "year",
help = 'The year',
action = 'store')
parser.add_argument('m',
type = int,
metavar = "month",
help = 'The month',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
create_curve_with_word_file(r, args.cvs, args.f, args.y, args.m)
if __name__ == "__main__":
main()

54
bin/tests/Wordsranking_Populate.py Executable file
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#!/usr/bin/python2.7
# -*-coding:UTF-8 -*
from packages.lib_words import *
from packages.imported import *
from pubsublogger import publisher
def main():
"""Main Function"""
parser = argparse.ArgumentParser(
description = 'Analysis Information Leak framework',
epilog = 'example : seq 2 | parallel ./Wordsranking_Populate.py -nbp 20')
parser.add_argument('-nbp',
type = int,
default = 200,
help = 'nbpaste',
action = 'store')
parser.add_argument('-db',
type = int,
default = 0,
help = 'The name of the Redis DB (default 0)',
choices=[0, 1, 2, 3, 4],
action = 'store')
parser.add_argument('-min',
type = int,
default = 4,
help = 'Minimum length of the inserted words (default 4)',
action = 'store')
parser.add_argument('-max',
type = int,
default = 200,
help = 'Maximum length of the inserted words (default 200)',
action = 'store')
args = parser.parse_args()
r = redis.StrictRedis(
host='localhost',
port=6379,
db=args.db)
p = r.pipeline(False)
publisher.channel = "youpi"
redis_words_ranking(p, r, args.nbp, args.min, args.max)
if __name__ == "__main__":
main()

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# Redis configuration file example
# Note on units: when memory size is needed, it is possible to specify
# it in the usual form of 1k 5GB 4M and so forth:
#
# 1k => 1000 bytes
# 1kb => 1024 bytes
# 1m => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# units are case insensitive so 1GB 1Gb 1gB are all the same.
################################## INCLUDES ###################################
# Include one or more other config files here. This is useful if you
# have a standard template that goes to all Redis server but also need
# to customize a few per-server settings. Include files can include
# other files, so use this wisely.
#
# Notice option "include" won't be rewritten by command "CONFIG REWRITE"
# from admin or Redis Sentinel. Since Redis always uses the last processed
# line as value of a configuration directive, you'd better put includes
# at the beginning of this file to avoid overwriting config change at runtime.
#
# If instead you are interested in using includes to override configuration
# options, it is better to use include as the last line.
#
# include /path/to/local.conf
# include /path/to/other.conf
################################ GENERAL #####################################
# By default Redis does not run as a daemon. Use 'yes' if you need it.
# Note that Redis will write a pid file in /var/run/redis.pid when daemonized.
daemonize no
# When running daemonized, Redis writes a pid file in /var/run/redis.pid by
# default. You can specify a custom pid file location here.
pidfile /var/run/redis.pid
# Accept connections on the specified port, default is 6379.
# If port 0 is specified Redis will not listen on a TCP socket.
port 6379
# TCP listen() backlog.
#
# In high requests-per-second environments you need an high backlog in order
# to avoid slow clients connections issues. Note that the Linux kernel
# will silently truncate it to the value of /proc/sys/net/core/somaxconn so
# make sure to raise both the value of somaxconn and tcp_max_syn_backlog
# in order to get the desired effect.
tcp-backlog 511
# By default Redis listens for connections from all the network interfaces
# available on the server. It is possible to listen to just one or multiple
# interfaces using the "bind" configuration directive, followed by one or
# more IP addresses.
#
# Examples:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1
# Specify the path for the Unix socket that will be used to listen for
# incoming connections. There is no default, so Redis will not listen
# on a unix socket when not specified.
#
unixsocket /tmp/redis.sock
unixsocketperm 755
# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
# TCP keepalive.
#
# If non-zero, use SO_KEEPALIVE to send TCP ACKs to clients in absence
# of communication. This is useful for two reasons:
#
# 1) Detect dead peers.
# 2) Take the connection alive from the point of view of network
# equipment in the middle.
#
# On Linux, the specified value (in seconds) is the period used to send ACKs.
# Note that to close the connection the double of the time is needed.
# On other kernels the period depends on the kernel configuration.
#
# A reasonable value for this option is 60 seconds.
tcp-keepalive 0
# Specify the server verbosity level.
# This can be one of:
# debug (a lot of information, useful for development/testing)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (moderately verbose, what you want in production probably)
# warning (only very important / critical messages are logged)
loglevel notice
# Specify the log file name. Also the empty string can be used to force
# Redis to log on the standard output. Note that if you use standard
# output for logging but daemonize, logs will be sent to /dev/null
logfile ""
# To enable logging to the system logger, just set 'syslog-enabled' to yes,
# and optionally update the other syslog parameters to suit your needs.
# syslog-enabled no
# Specify the syslog identity.
# syslog-ident redis
# Specify the syslog facility. Must be USER or between LOCAL0-LOCAL7.
# syslog-facility local0
# Set the number of databases. The default database is DB 0, you can select
# a different one on a per-connection basis using SELECT <dbid> where
# dbid is a number between 0 and 'databases'-1
databases 16
################################ SNAPSHOTTING ################################
#
# Save the DB on disk:
#
# save <seconds> <changes>
#
# Will save the DB if both the given number of seconds and the given
# number of write operations against the DB occurred.
#
# In the example below the behaviour will be to save:
# after 900 sec (15 min) if at least 1 key changed
# after 300 sec (5 min) if at least 10 keys changed
# after 60 sec if at least 10000 keys changed
#
# Note: you can disable saving at all commenting all the "save" lines.
#
# It is also possible to remove all the previously configured save
# points by adding a save directive with a single empty string argument
# like in the following example:
#
# save ""
#save 900 1
#save 300 10
#save 60 10000
# By default Redis will stop accepting writes if RDB snapshots are enabled
# (at least one save point) and the latest background save failed.
# This will make the user aware (in a hard way) that data is not persisting
# on disk properly, otherwise chances are that no one will notice and some
# disaster will happen.
#
# If the background saving process will start working again Redis will
# automatically allow writes again.
#
# However if you have setup your proper monitoring of the Redis server
# and persistence, you may want to disable this feature so that Redis will
# continue to work as usual even if there are problems with disk,
# permissions, and so forth.
stop-writes-on-bgsave-error yes
# Compress string objects using LZF when dump .rdb databases?
# For default that's set to 'yes' as it's almost always a win.
# If you want to save some CPU in the saving child set it to 'no' but
# the dataset will likely be bigger if you have compressible values or keys.
rdbcompression yes
# Since version 5 of RDB a CRC64 checksum is placed at the end of the file.
# This makes the format more resistant to corruption but there is a performance
# hit to pay (around 10%) when saving and loading RDB files, so you can disable it
# for maximum performances.
#
# RDB files created with checksum disabled have a checksum of zero that will
# tell the loading code to skip the check.
rdbchecksum yes
# The filename where to dump the DB
dbfilename dump.rdb
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the 'dbfilename' configuration directive.
#
# The Append Only File will also be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir /home/user/dumps/
################################# REPLICATION #################################
# Master-Slave replication. Use slaveof to make a Redis instance a copy of
# another Redis server. Note that the configuration is local to the slave
# so for example it is possible to configure the slave to save the DB with a
# different interval, or to listen to another port, and so on.
#
# slaveof <masterip> <masterport>
# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the slave to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the slave request.
#
# masterauth <master-password>
# When a slave loses its connection with the master, or when the replication
# is still in progress, the slave can act in two different ways:
#
# 1) if slave-serve-stale-data is set to 'yes' (the default) the slave will
# still reply to client requests, possibly with out of date data, or the
# data set may just be empty if this is the first synchronization.
#
# 2) if slave-serve-stale-data is set to 'no' the slave will reply with
# an error "SYNC with master in progress" to all the kind of commands
# but to INFO and SLAVEOF.
#
slave-serve-stale-data yes
# You can configure a slave instance to accept writes or not. Writing against
# a slave instance may be useful to store some ephemeral data (because data
# written on a slave will be easily deleted after resync with the master) but
# may also cause problems if clients are writing to it because of a
# misconfiguration.
#
# Since Redis 2.6 by default slaves are read-only.
#
# Note: read only slaves are not designed to be exposed to untrusted clients
# on the internet. It's just a protection layer against misuse of the instance.
# Still a read only slave exports by default all the administrative commands
# such as CONFIG, DEBUG, and so forth. To a limited extent you can improve
# security of read only slaves using 'rename-command' to shadow all the
# administrative / dangerous commands.
slave-read-only yes
# Slaves send PINGs to server in a predefined interval. It's possible to change
# this interval with the repl_ping_slave_period option. The default value is 10
# seconds.
#
# repl-ping-slave-period 10
# The following option sets the replication timeout for:
#
# 1) Bulk transfer I/O during SYNC, from the point of view of slave.
# 2) Master timeout from the point of view of slaves (data, pings).
# 3) Slave timeout from the point of view of masters (REPLCONF ACK pings).
#
# It is important to make sure that this value is greater than the value
# specified for repl-ping-slave-period otherwise a timeout will be detected
# every time there is low traffic between the master and the slave.
#
# repl-timeout 60
# Disable TCP_NODELAY on the slave socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to slaves. But this can add a delay for
# the data to appear on the slave side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the slave side will
# be reduced but more bandwidth will be used for replication.
#
# By default we optimize for low latency, but in very high traffic conditions
# or when the master and slaves are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
# Set the replication backlog size. The backlog is a buffer that accumulates
# slave data when slaves are disconnected for some time, so that when a slave
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the slave missed while
# disconnected.
#
# The biggest the replication backlog, the longer the time the slave can be
# disconnected and later be able to perform a partial resynchronization.
#
# The backlog is only allocated once there is at least a slave connected.
#
# repl-backlog-size 1mb
# After a master has no longer connected slaves for some time, the backlog
# will be freed. The following option configures the amount of seconds that
# need to elapse, starting from the time the last slave disconnected, for
# the backlog buffer to be freed.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600
# The slave priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a slave to promote into a
# master if the master is no longer working correctly.
#
# A slave with a low priority number is considered better for promotion, so
# for instance if there are three slaves with priority 10, 100, 25 Sentinel will
# pick the one with priority 10, that is the lowest.
#
# However a special priority of 0 marks the slave as not able to perform the
# role of master, so a slave with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 100.
slave-priority 100
# It is possible for a master to stop accepting writes if there are less than
# N slaves connected, having a lag less or equal than M seconds.
#
# The N slaves need to be in "online" state.
#
# The lag in seconds, that must be <= the specified value, is calculated from
# the last ping received from the slave, that is usually sent every second.
#
# This option does not GUARANTEES that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough slaves
# are available, to the specified number of seconds.
#
# For example to require at least 3 slaves with a lag <= 10 seconds use:
#
# min-slaves-to-write 3
# min-slaves-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-slaves-to-write is set to 0 (feature disabled) and
# min-slaves-max-lag is set to 10.
################################## SECURITY ###################################
# Require clients to issue AUTH <PASSWORD> before processing any other
# commands. This might be useful in environments in which you do not trust
# others with access to the host running redis-server.
#
# This should stay commented out for backward compatibility and because most
# people do not need auth (e.g. they run their own servers).
#
# Warning: since Redis is pretty fast an outside user can try up to
# 150k passwords per second against a good box. This means that you should
# use a very strong password otherwise it will be very easy to break.
#
# requirepass foobared
# Command renaming.
#
# It is possible to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# hard to guess so that it will still be available for internal-use tools
# but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possible to completely kill a command by renaming it into
# an empty string:
#
# rename-command CONFIG ""
#
# Please note that changing the name of commands that are logged into the
# AOF file or transmitted to slaves may cause problems.
################################### LIMITS ####################################
# Set the max number of connected clients at the same time. By default
# this limit is set to 10000 clients, however if the Redis server is not
# able to configure the process file limit to allow for the specified limit
# the max number of allowed clients is set to the current file limit
# minus 32 (as Redis reserves a few file descriptors for internal uses).
#
# Once the limit is reached Redis will close all the new connections sending
# an error 'max number of clients reached'.
#
# maxclients 10000
# Don't use more memory than the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys
# according to the eviction policy selected (see maxmemory-policy).
#
# If Redis can't remove keys according to the policy, or if the policy is
# set to 'noeviction', Redis will start to reply with errors to commands
# that would use more memory, like SET, LPUSH, and so on, and will continue
# to reply to read-only commands like GET.
#
# This option is usually useful when using Redis as an LRU cache, or to set
# a hard memory limit for an instance (using the 'noeviction' policy).
#
# WARNING: If you have slaves attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the slaves are subtracted
# from the used memory count, so that network problems / resyncs will
# not trigger a loop where keys are evicted, and in turn the output
# buffer of slaves is full with DELs of keys evicted triggering the deletion
# of more keys, and so forth until the database is completely emptied.
#
# In short... if you have slaves attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for slave
# output buffers (but this is not needed if the policy is 'noeviction').
#
# maxmemory <bytes>
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# allkeys-lru -> remove any key accordingly to the LRU algorithm
# volatile-random -> remove a random key with an expire set
# allkeys-random -> remove a random key, any key
# volatile-ttl -> remove the key with the nearest expire time (minor TTL)
# noeviction -> don't expire at all, just return an error on write operations
#
# Note: with any of the above policies, Redis will return an error on write
# operations, when there are not suitable keys for eviction.
#
# At the date of writing this commands are: set setnx setex append
# incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
# sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
# zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
# getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy volatile-lru
# LRU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can select as well the sample
# size to check. For instance for default Redis will check three keys and
# pick the one that was used less recently, you can change the sample size
# using the following configuration directive.
#
# maxmemory-samples 3
############################## APPEND ONLY MODE ###############################
# By default Redis asynchronously dumps the dataset on disk. This mode is
# good enough in many applications, but an issue with the Redis process or
# a power outage may result into a few minutes of writes lost (depending on
# the configured save points).
#
# The Append Only File is an alternative persistence mode that provides
# much better durability. For instance using the default data fsync policy
# (see later in the config file) Redis can lose just one second of writes in a
# dramatic event like a server power outage, or a single write if something
# wrong with the Redis process itself happens, but the operating system is
# still running correctly.
#
# AOF and RDB persistence can be enabled at the same time without problems.
# If the AOF is enabled on startup Redis will load the AOF, that is the file
# with the better durability guarantees.
#
# Please check http://redis.io/topics/persistence for more information.
appendonly no
# The name of the append only file (default: "appendonly.aof")
appendfilename "appendonly.aof"
# The fsync() call tells the Operating System to actually write data on disk
# instead to wait for more data in the output buffer. Some OS will really flush
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log . Slow, Safest.
# everysec: fsync only one time every second. Compromise.
#
# The default is "everysec", as that's usually the right compromise between
# speed and data safety. It's up to you to understand if you can relax this to
# "no" that will let the operating system flush the output buffer when
# it wants, for better performances (but if you can live with the idea of
# some data loss consider the default persistence mode that's snapshotting),
# or on the contrary, use "always" that's very slow but a bit safer than
# everysec.
#
# More details please check the following article:
# http://antirez.com/post/redis-persistence-demystified.html
#
# If unsure, use "everysec".
# appendfsync always
appendfsync everysec
# appendfsync no
# When the AOF fsync policy is set to always or everysec, and a background
# saving process (a background save or AOF log background rewriting) is
# performing a lot of I/O against the disk, in some Linux configurations
# Redis may block too long on the fsync() call. Note that there is no fix for
# this currently, as even performing fsync in a different thread will block
# our synchronous write(2) call.
#
# In order to mitigate this problem it's possible to use the following option
# that will prevent fsync() from being called in the main process while a
# BGSAVE or BGREWRITEAOF is in progress.
#
# This means that while another child is saving, the durability of Redis is
# the same as "appendfsync none". In practical terms, this means that it is
# possible to lose up to 30 seconds of log in the worst scenario (with the
# default Linux settings).
#
# If you have latency problems turn this to "yes". Otherwise leave it as
# "no" that is the safest pick from the point of view of durability.
no-appendfsync-on-rewrite no
# Automatic rewrite of the append only file.
# Redis is able to automatically rewrite the log file implicitly calling
# BGREWRITEAOF when the AOF log size grows by the specified percentage.
#
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (if no rewrite has happened since the restart, the size of
# the AOF at startup is used).
#
# This base size is compared to the current size. If the current size is
# bigger than the specified percentage, the rewrite is triggered. Also
# you need to specify a minimal size for the AOF file to be rewritten, this
# is useful to avoid rewriting the AOF file even if the percentage increase
# is reached but it is still pretty small.
#
# Specify a percentage of zero in order to disable the automatic AOF
# rewrite feature.
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb
################################ LUA SCRIPTING ###############################
# Max execution time of a Lua script in milliseconds.
#
# If the maximum execution time is reached Redis will log that a script is
# still in execution after the maximum allowed time and will start to
# reply to queries with an error.
#
# When a long running script exceed the maximum execution time only the
# SCRIPT KILL and SHUTDOWN NOSAVE commands are available. The first can be
# used to stop a script that did not yet called write commands. The second
# is the only way to shut down the server in the case a write commands was
# already issue by the script but the user don't want to wait for the natural
# termination of the script.
#
# Set it to 0 or a negative value for unlimited execution without warnings.
lua-time-limit 5000
################################## SLOW LOG ###################################
# The Redis Slow Log is a system to log queries that exceeded a specified
# execution time. The execution time does not include the I/O operations
# like talking with the client, sending the reply and so forth,
# but just the time needed to actually execute the command (this is the only
# stage of command execution where the thread is blocked and can not serve
# other requests in the meantime).
#
# You can configure the slow log with two parameters: one tells Redis
# what is the execution time, in microseconds, to exceed in order for the
# command to get logged, and the other parameter is the length of the
# slow log. When a new command is logged the oldest one is removed from the
# queue of logged commands.
# The following time is expressed in microseconds, so 1000000 is equivalent
# to one second. Note that a negative number disables the slow log, while
# a value of zero forces the logging of every command.
slowlog-log-slower-than 10000
# There is no limit to this length. Just be aware that it will consume memory.
# You can reclaim memory used by the slow log with SLOWLOG RESET.
slowlog-max-len 128
############################# Event notification ##############################
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/keyspace-events
#
# For instance if keyspace events notification is enabled, and a client
# performs a DEL operation on key "foo" stored in the Database 0, two
# messages will be published via Pub/Sub:
#
# PUBLISH __keyspace@0__:foo del
# PUBLISH __keyevent@0__:del foo
#
# It is possible to select the events that Redis will notify among a set
# of classes. Every class is identified by a single character:
#
# K Keyspace events, published with __keyspace@<db>__ prefix.
# E Keyevent events, published with __keyevent@<db>__ prefix.
# g Generic commands (non-type specific) like DEL, EXPIRE, RENAME, ...
# $ String commands
# l List commands
# s Set commands
# h Hash commands
# z Sorted set commands
# x Expired events (events generated every time a key expires)
# e Evicted events (events generated when a key is evicted for maxmemory)
# A Alias for g$lshzxe, so that the "AKE" string means all the events.
#
# The "notify-keyspace-events" takes as argument a string that is composed
# by zero or multiple characters. The empty string means that notifications
# are disabled at all.
#
# Example: to enable list and generic events, from the point of view of the
# event name, use:
#
# notify-keyspace-events Elg
#
# Example 2: to get the stream of the expired keys subscribing to channel
# name __keyevent@0__:expired use:
#
# notify-keyspace-events Ex
#
# By default all notifications are disabled because most users don't need
# this feature and the feature has some overhead. Note that if you don't
# specify at least one of K or E, no events will be delivered.
notify-keyspace-events ""
############################### ADVANCED CONFIG ###############################
# Hashes are encoded using a memory efficient data structure when they have a
# small number of entries, and the biggest entry does not exceed a given
# threshold. These thresholds can be configured using the following directives.
hash-max-ziplist-entries 512
hash-max-ziplist-value 64
# Similarly to hashes, small lists are also encoded in a special way in order
# to save a lot of space. The special representation is only used when
# you are under the following limits:
list-max-ziplist-entries 512
list-max-ziplist-value 64
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happens to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512
# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64
# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
# order to help rehashing the main Redis hash table (the one mapping top-level
# keys to values). The hash table implementation Redis uses (see dict.c)
# performs a lazy rehashing: the more operation you run into a hash table
# that is rehashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
#
# The default is to use this millisecond 10 times every second in order to
# active rehashing the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply form time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes
# The client output buffer limits can be used to force disconnection of clients
# that are not reading data from the server fast enough for some reason (a
# common reason is that a Pub/Sub client can't consume messages as fast as the
# publisher can produce them).
#
# The limit can be set differently for the three different classes of clients:
#
# normal -> normal clients
# slave -> slave clients and MONITOR clients
# pubsub -> clients subscribed to at least one pubsub channel or pattern
#
# The syntax of every client-output-buffer-limit directive is the following:
#
# client-output-buffer-limit <class> <hard limit> <soft limit> <soft seconds>
#
# A client is immediately disconnected once the hard limit is reached, or if
# the soft limit is reached and remains reached for the specified number of
# seconds (continuously).
# So for instance if the hard limit is 32 megabytes and the soft limit is
# 16 megabytes / 10 seconds, the client will get disconnected immediately
# if the size of the output buffers reach 32 megabytes, but will also get
# disconnected if the client reaches 16 megabytes and continuously overcomes
# the limit for 10 seconds.
#
# By default normal clients are not limited because they don't receive data
# without asking (in a push way), but just after a request, so only
# asynchronous clients may create a scenario where data is requested faster
# than it can read.
#
# Instead there is a default limit for pubsub and slave clients, since
# subscribers and slaves receive data in a push fashion.
#
# Both the hard or the soft limit can be disabled by setting them to zero.
client-output-buffer-limit normal 0 0 0
client-output-buffer-limit slave 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
# Redis calls an internal function to perform many background tasks, like
# closing connections of clients in timeout, purging expired keys that are
# never requested, and so forth.
#
# Not all tasks are performed with the same frequency, but Redis checks for
# tasks to perform accordingly to the specified "hz" value.
#
# By default "hz" is set to 10. Raising the value will use more CPU when
# Redis is idle, but at the same time will make Redis more responsive when
# there are many keys expiring at the same time, and timeouts may be
# handled with more precision.
#
# The range is between 1 and 500, however a value over 100 is usually not
# a good idea. Most users should use the default of 10 and raise this up to
# 100 only in environments where very low latency is required.
hz 10
# When a child rewrites the AOF file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
aof-rewrite-incremental-fsync yes

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# Redis configuration file example
# Note on units: when memory size is needed, it is possible to specify
# it in the usual form of 1k 5GB 4M and so forth:
#
# 1k => 1000 bytes
# 1kb => 1024 bytes
# 1m => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# units are case insensitive so 1GB 1Gb 1gB are all the same.
################################## INCLUDES ###################################
# Include one or more other config files here. This is useful if you
# have a standard template that goes to all Redis server but also need
# to customize a few per-server settings. Include files can include
# other files, so use this wisely.
#
# Notice option "include" won't be rewritten by command "CONFIG REWRITE"
# from admin or Redis Sentinel. Since Redis always uses the last processed
# line as value of a configuration directive, you'd better put includes
# at the beginning of this file to avoid overwriting config change at runtime.
#
# If instead you are interested in using includes to override configuration
# options, it is better to use include as the last line.
#
# include /path/to/local.conf
# include /path/to/other.conf
################################ GENERAL #####################################
# By default Redis does not run as a daemon. Use 'yes' if you need it.
# Note that Redis will write a pid file in /var/run/redis.pid when daemonized.
daemonize no
# When running daemonized, Redis writes a pid file in /var/run/redis.pid by
# default. You can specify a custom pid file location here.
pidfile /var/run/redis.pid
# Accept connections on the specified port, default is 6379.
# If port 0 is specified Redis will not listen on a TCP socket.
port 6380
# TCP listen() backlog.
#
# In high requests-per-second environments you need an high backlog in order
# to avoid slow clients connections issues. Note that the Linux kernel
# will silently truncate it to the value of /proc/sys/net/core/somaxconn so
# make sure to raise both the value of somaxconn and tcp_max_syn_backlog
# in order to get the desired effect.
tcp-backlog 511
# By default Redis listens for connections from all the network interfaces
# available on the server. It is possible to listen to just one or multiple
# interfaces using the "bind" configuration directive, followed by one or
# more IP addresses.
#
# Examples:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1
# Specify the path for the Unix socket that will be used to listen for
# incoming connections. There is no default, so Redis will not listen
# on a unix socket when not specified.
#
unixsocket /tmp/redis.sock
unixsocketperm 755
# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
# TCP keepalive.
#
# If non-zero, use SO_KEEPALIVE to send TCP ACKs to clients in absence
# of communication. This is useful for two reasons:
#
# 1) Detect dead peers.
# 2) Take the connection alive from the point of view of network
# equipment in the middle.
#
# On Linux, the specified value (in seconds) is the period used to send ACKs.
# Note that to close the connection the double of the time is needed.
# On other kernels the period depends on the kernel configuration.
#
# A reasonable value for this option is 60 seconds.
tcp-keepalive 0
# Specify the server verbosity level.
# This can be one of:
# debug (a lot of information, useful for development/testing)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (moderately verbose, what you want in production probably)
# warning (only very important / critical messages are logged)
loglevel notice
# Specify the log file name. Also the empty string can be used to force
# Redis to log on the standard output. Note that if you use standard
# output for logging but daemonize, logs will be sent to /dev/null
logfile ""
# To enable logging to the system logger, just set 'syslog-enabled' to yes,
# and optionally update the other syslog parameters to suit your needs.
# syslog-enabled no
# Specify the syslog identity.
# syslog-ident redis
# Specify the syslog facility. Must be USER or between LOCAL0-LOCAL7.
# syslog-facility local0
# Set the number of databases. The default database is DB 0, you can select
# a different one on a per-connection basis using SELECT <dbid> where
# dbid is a number between 0 and 'databases'-1
databases 16
################################ SNAPSHOTTING ################################
#
# Save the DB on disk:
#
# save <seconds> <changes>
#
# Will save the DB if both the given number of seconds and the given
# number of write operations against the DB occurred.
#
# In the example below the behaviour will be to save:
# after 900 sec (15 min) if at least 1 key changed
# after 300 sec (5 min) if at least 10 keys changed
# after 60 sec if at least 10000 keys changed
#
# Note: you can disable saving at all commenting all the "save" lines.
#
# It is also possible to remove all the previously configured save
# points by adding a save directive with a single empty string argument
# like in the following example:
#
# save ""
#save 900 1
#save 300 10
#save 60 10000
# By default Redis will stop accepting writes if RDB snapshots are enabled
# (at least one save point) and the latest background save failed.
# This will make the user aware (in a hard way) that data is not persisting
# on disk properly, otherwise chances are that no one will notice and some
# disaster will happen.
#
# If the background saving process will start working again Redis will
# automatically allow writes again.
#
# However if you have setup your proper monitoring of the Redis server
# and persistence, you may want to disable this feature so that Redis will
# continue to work as usual even if there are problems with disk,
# permissions, and so forth.
stop-writes-on-bgsave-error yes
# Compress string objects using LZF when dump .rdb databases?
# For default that's set to 'yes' as it's almost always a win.
# If you want to save some CPU in the saving child set it to 'no' but
# the dataset will likely be bigger if you have compressible values or keys.
rdbcompression yes
# Since version 5 of RDB a CRC64 checksum is placed at the end of the file.
# This makes the format more resistant to corruption but there is a performance
# hit to pay (around 10%) when saving and loading RDB files, so you can disable it
# for maximum performances.
#
# RDB files created with checksum disabled have a checksum of zero that will
# tell the loading code to skip the check.
rdbchecksum yes
# The filename where to dump the DB
dbfilename dump2.rdb
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the 'dbfilename' configuration directive.
#
# The Append Only File will also be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir /home/user/dumps/
################################# REPLICATION #################################
# Master-Slave replication. Use slaveof to make a Redis instance a copy of
# another Redis server. Note that the configuration is local to the slave
# so for example it is possible to configure the slave to save the DB with a
# different interval, or to listen to another port, and so on.
#
# slaveof <masterip> <masterport>
# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the slave to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the slave request.
#
# masterauth <master-password>
# When a slave loses its connection with the master, or when the replication
# is still in progress, the slave can act in two different ways:
#
# 1) if slave-serve-stale-data is set to 'yes' (the default) the slave will
# still reply to client requests, possibly with out of date data, or the
# data set may just be empty if this is the first synchronization.
#
# 2) if slave-serve-stale-data is set to 'no' the slave will reply with
# an error "SYNC with master in progress" to all the kind of commands
# but to INFO and SLAVEOF.
#
slave-serve-stale-data yes
# You can configure a slave instance to accept writes or not. Writing against
# a slave instance may be useful to store some ephemeral data (because data
# written on a slave will be easily deleted after resync with the master) but
# may also cause problems if clients are writing to it because of a
# misconfiguration.
#
# Since Redis 2.6 by default slaves are read-only.
#
# Note: read only slaves are not designed to be exposed to untrusted clients
# on the internet. It's just a protection layer against misuse of the instance.
# Still a read only slave exports by default all the administrative commands
# such as CONFIG, DEBUG, and so forth. To a limited extent you can improve
# security of read only slaves using 'rename-command' to shadow all the
# administrative / dangerous commands.
slave-read-only yes
# Slaves send PINGs to server in a predefined interval. It's possible to change
# this interval with the repl_ping_slave_period option. The default value is 10
# seconds.
#
# repl-ping-slave-period 10
# The following option sets the replication timeout for:
#
# 1) Bulk transfer I/O during SYNC, from the point of view of slave.
# 2) Master timeout from the point of view of slaves (data, pings).
# 3) Slave timeout from the point of view of masters (REPLCONF ACK pings).
#
# It is important to make sure that this value is greater than the value
# specified for repl-ping-slave-period otherwise a timeout will be detected
# every time there is low traffic between the master and the slave.
#
# repl-timeout 60
# Disable TCP_NODELAY on the slave socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to slaves. But this can add a delay for
# the data to appear on the slave side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the slave side will
# be reduced but more bandwidth will be used for replication.
#
# By default we optimize for low latency, but in very high traffic conditions
# or when the master and slaves are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
# Set the replication backlog size. The backlog is a buffer that accumulates
# slave data when slaves are disconnected for some time, so that when a slave
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the slave missed while
# disconnected.
#
# The biggest the replication backlog, the longer the time the slave can be
# disconnected and later be able to perform a partial resynchronization.
#
# The backlog is only allocated once there is at least a slave connected.
#
# repl-backlog-size 1mb
# After a master has no longer connected slaves for some time, the backlog
# will be freed. The following option configures the amount of seconds that
# need to elapse, starting from the time the last slave disconnected, for
# the backlog buffer to be freed.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600
# The slave priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a slave to promote into a
# master if the master is no longer working correctly.
#
# A slave with a low priority number is considered better for promotion, so
# for instance if there are three slaves with priority 10, 100, 25 Sentinel will
# pick the one with priority 10, that is the lowest.
#
# However a special priority of 0 marks the slave as not able to perform the
# role of master, so a slave with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 100.
slave-priority 100
# It is possible for a master to stop accepting writes if there are less than
# N slaves connected, having a lag less or equal than M seconds.
#
# The N slaves need to be in "online" state.
#
# The lag in seconds, that must be <= the specified value, is calculated from
# the last ping received from the slave, that is usually sent every second.
#
# This option does not GUARANTEES that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough slaves
# are available, to the specified number of seconds.
#
# For example to require at least 3 slaves with a lag <= 10 seconds use:
#
# min-slaves-to-write 3
# min-slaves-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-slaves-to-write is set to 0 (feature disabled) and
# min-slaves-max-lag is set to 10.
################################## SECURITY ###################################
# Require clients to issue AUTH <PASSWORD> before processing any other
# commands. This might be useful in environments in which you do not trust
# others with access to the host running redis-server.
#
# This should stay commented out for backward compatibility and because most
# people do not need auth (e.g. they run their own servers).
#
# Warning: since Redis is pretty fast an outside user can try up to
# 150k passwords per second against a good box. This means that you should
# use a very strong password otherwise it will be very easy to break.
#
# requirepass foobared
# Command renaming.
#
# It is possible to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# hard to guess so that it will still be available for internal-use tools
# but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possible to completely kill a command by renaming it into
# an empty string:
#
# rename-command CONFIG ""
#
# Please note that changing the name of commands that are logged into the
# AOF file or transmitted to slaves may cause problems.
################################### LIMITS ####################################
# Set the max number of connected clients at the same time. By default
# this limit is set to 10000 clients, however if the Redis server is not
# able to configure the process file limit to allow for the specified limit
# the max number of allowed clients is set to the current file limit
# minus 32 (as Redis reserves a few file descriptors for internal uses).
#
# Once the limit is reached Redis will close all the new connections sending
# an error 'max number of clients reached'.
#
# maxclients 10000
# Don't use more memory than the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys
# according to the eviction policy selected (see maxmemory-policy).
#
# If Redis can't remove keys according to the policy, or if the policy is
# set to 'noeviction', Redis will start to reply with errors to commands
# that would use more memory, like SET, LPUSH, and so on, and will continue
# to reply to read-only commands like GET.
#
# This option is usually useful when using Redis as an LRU cache, or to set
# a hard memory limit for an instance (using the 'noeviction' policy).
#
# WARNING: If you have slaves attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the slaves are subtracted
# from the used memory count, so that network problems / resyncs will
# not trigger a loop where keys are evicted, and in turn the output
# buffer of slaves is full with DELs of keys evicted triggering the deletion
# of more keys, and so forth until the database is completely emptied.
#
# In short... if you have slaves attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for slave
# output buffers (but this is not needed if the policy is 'noeviction').
#
# maxmemory <bytes>
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# allkeys-lru -> remove any key accordingly to the LRU algorithm
# volatile-random -> remove a random key with an expire set
# allkeys-random -> remove a random key, any key
# volatile-ttl -> remove the key with the nearest expire time (minor TTL)
# noeviction -> don't expire at all, just return an error on write operations
#
# Note: with any of the above policies, Redis will return an error on write
# operations, when there are not suitable keys for eviction.
#
# At the date of writing this commands are: set setnx setex append
# incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
# sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
# zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
# getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy volatile-lru
# LRU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can select as well the sample
# size to check. For instance for default Redis will check three keys and
# pick the one that was used less recently, you can change the sample size
# using the following configuration directive.
#
# maxmemory-samples 3
############################## APPEND ONLY MODE ###############################
# By default Redis asynchronously dumps the dataset on disk. This mode is
# good enough in many applications, but an issue with the Redis process or
# a power outage may result into a few minutes of writes lost (depending on
# the configured save points).
#
# The Append Only File is an alternative persistence mode that provides
# much better durability. For instance using the default data fsync policy
# (see later in the config file) Redis can lose just one second of writes in a
# dramatic event like a server power outage, or a single write if something
# wrong with the Redis process itself happens, but the operating system is
# still running correctly.
#
# AOF and RDB persistence can be enabled at the same time without problems.
# If the AOF is enabled on startup Redis will load the AOF, that is the file
# with the better durability guarantees.
#
# Please check http://redis.io/topics/persistence for more information.
appendonly no
# The name of the append only file (default: "appendonly.aof")
appendfilename "appendonly.aof"
# The fsync() call tells the Operating System to actually write data on disk
# instead to wait for more data in the output buffer. Some OS will really flush
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log . Slow, Safest.
# everysec: fsync only one time every second. Compromise.
#
# The default is "everysec", as that's usually the right compromise between
# speed and data safety. It's up to you to understand if you can relax this to
# "no" that will let the operating system flush the output buffer when
# it wants, for better performances (but if you can live with the idea of
# some data loss consider the default persistence mode that's snapshotting),
# or on the contrary, use "always" that's very slow but a bit safer than
# everysec.
#
# More details please check the following article:
# http://antirez.com/post/redis-persistence-demystified.html
#
# If unsure, use "everysec".
# appendfsync always
appendfsync everysec
# appendfsync no
# When the AOF fsync policy is set to always or everysec, and a background
# saving process (a background save or AOF log background rewriting) is
# performing a lot of I/O against the disk, in some Linux configurations
# Redis may block too long on the fsync() call. Note that there is no fix for
# this currently, as even performing fsync in a different thread will block
# our synchronous write(2) call.
#
# In order to mitigate this problem it's possible to use the following option
# that will prevent fsync() from being called in the main process while a
# BGSAVE or BGREWRITEAOF is in progress.
#
# This means that while another child is saving, the durability of Redis is
# the same as "appendfsync none". In practical terms, this means that it is
# possible to lose up to 30 seconds of log in the worst scenario (with the
# default Linux settings).
#
# If you have latency problems turn this to "yes". Otherwise leave it as
# "no" that is the safest pick from the point of view of durability.
no-appendfsync-on-rewrite no
# Automatic rewrite of the append only file.
# Redis is able to automatically rewrite the log file implicitly calling
# BGREWRITEAOF when the AOF log size grows by the specified percentage.
#
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (if no rewrite has happened since the restart, the size of
# the AOF at startup is used).
#
# This base size is compared to the current size. If the current size is
# bigger than the specified percentage, the rewrite is triggered. Also
# you need to specify a minimal size for the AOF file to be rewritten, this
# is useful to avoid rewriting the AOF file even if the percentage increase
# is reached but it is still pretty small.
#
# Specify a percentage of zero in order to disable the automatic AOF
# rewrite feature.
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb
################################ LUA SCRIPTING ###############################
# Max execution time of a Lua script in milliseconds.
#
# If the maximum execution time is reached Redis will log that a script is
# still in execution after the maximum allowed time and will start to
# reply to queries with an error.
#
# When a long running script exceed the maximum execution time only the
# SCRIPT KILL and SHUTDOWN NOSAVE commands are available. The first can be
# used to stop a script that did not yet called write commands. The second
# is the only way to shut down the server in the case a write commands was
# already issue by the script but the user don't want to wait for the natural
# termination of the script.
#
# Set it to 0 or a negative value for unlimited execution without warnings.
lua-time-limit 5000
################################## SLOW LOG ###################################
# The Redis Slow Log is a system to log queries that exceeded a specified
# execution time. The execution time does not include the I/O operations
# like talking with the client, sending the reply and so forth,
# but just the time needed to actually execute the command (this is the only
# stage of command execution where the thread is blocked and can not serve
# other requests in the meantime).
#
# You can configure the slow log with two parameters: one tells Redis
# what is the execution time, in microseconds, to exceed in order for the
# command to get logged, and the other parameter is the length of the
# slow log. When a new command is logged the oldest one is removed from the
# queue of logged commands.
# The following time is expressed in microseconds, so 1000000 is equivalent
# to one second. Note that a negative number disables the slow log, while
# a value of zero forces the logging of every command.
slowlog-log-slower-than 10000
# There is no limit to this length. Just be aware that it will consume memory.
# You can reclaim memory used by the slow log with SLOWLOG RESET.
slowlog-max-len 128
############################# Event notification ##############################
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/keyspace-events
#
# For instance if keyspace events notification is enabled, and a client
# performs a DEL operation on key "foo" stored in the Database 0, two
# messages will be published via Pub/Sub:
#
# PUBLISH __keyspace@0__:foo del
# PUBLISH __keyevent@0__:del foo
#
# It is possible to select the events that Redis will notify among a set
# of classes. Every class is identified by a single character:
#
# K Keyspace events, published with __keyspace@<db>__ prefix.
# E Keyevent events, published with __keyevent@<db>__ prefix.
# g Generic commands (non-type specific) like DEL, EXPIRE, RENAME, ...
# $ String commands
# l List commands
# s Set commands
# h Hash commands
# z Sorted set commands
# x Expired events (events generated every time a key expires)
# e Evicted events (events generated when a key is evicted for maxmemory)
# A Alias for g$lshzxe, so that the "AKE" string means all the events.
#
# The "notify-keyspace-events" takes as argument a string that is composed
# by zero or multiple characters. The empty string means that notifications
# are disabled at all.
#
# Example: to enable list and generic events, from the point of view of the
# event name, use:
#
# notify-keyspace-events Elg
#
# Example 2: to get the stream of the expired keys subscribing to channel
# name __keyevent@0__:expired use:
#
# notify-keyspace-events Ex
#
# By default all notifications are disabled because most users don't need
# this feature and the feature has some overhead. Note that if you don't
# specify at least one of K or E, no events will be delivered.
notify-keyspace-events ""
############################### ADVANCED CONFIG ###############################
# Hashes are encoded using a memory efficient data structure when they have a
# small number of entries, and the biggest entry does not exceed a given
# threshold. These thresholds can be configured using the following directives.
hash-max-ziplist-entries 512
hash-max-ziplist-value 64
# Similarly to hashes, small lists are also encoded in a special way in order
# to save a lot of space. The special representation is only used when
# you are under the following limits:
list-max-ziplist-entries 512
list-max-ziplist-value 64
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happens to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512
# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64
# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
# order to help rehashing the main Redis hash table (the one mapping top-level
# keys to values). The hash table implementation Redis uses (see dict.c)
# performs a lazy rehashing: the more operation you run into a hash table
# that is rehashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
#
# The default is to use this millisecond 10 times every second in order to
# active rehashing the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply form time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes
# The client output buffer limits can be used to force disconnection of clients
# that are not reading data from the server fast enough for some reason (a
# common reason is that a Pub/Sub client can't consume messages as fast as the
# publisher can produce them).
#
# The limit can be set differently for the three different classes of clients:
#
# normal -> normal clients
# slave -> slave clients and MONITOR clients
# pubsub -> clients subscribed to at least one pubsub channel or pattern
#
# The syntax of every client-output-buffer-limit directive is the following:
#
# client-output-buffer-limit <class> <hard limit> <soft limit> <soft seconds>
#
# A client is immediately disconnected once the hard limit is reached, or if
# the soft limit is reached and remains reached for the specified number of
# seconds (continuously).
# So for instance if the hard limit is 32 megabytes and the soft limit is
# 16 megabytes / 10 seconds, the client will get disconnected immediately
# if the size of the output buffers reach 32 megabytes, but will also get
# disconnected if the client reaches 16 megabytes and continuously overcomes
# the limit for 10 seconds.
#
# By default normal clients are not limited because they don't receive data
# without asking (in a push way), but just after a request, so only
# asynchronous clients may create a scenario where data is requested faster
# than it can read.
#
# Instead there is a default limit for pubsub and slave clients, since
# subscribers and slaves receive data in a push fashion.
#
# Both the hard or the soft limit can be disabled by setting them to zero.
client-output-buffer-limit normal 0 0 0
client-output-buffer-limit slave 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
# Redis calls an internal function to perform many background tasks, like
# closing connections of clients in timeout, purging expired keys that are
# never requested, and so forth.
#
# Not all tasks are performed with the same frequency, but Redis checks for
# tasks to perform accordingly to the specified "hz" value.
#
# By default "hz" is set to 10. Raising the value will use more CPU when
# Redis is idle, but at the same time will make Redis more responsive when
# there are many keys expiring at the same time, and timeouts may be
# handled with more precision.
#
# The range is between 1 and 500, however a value over 100 is usually not
# a good idea. Most users should use the default of 10 and raise this up to
# 100 only in environments where very low latency is required.
hz 10
# When a child rewrites the AOF file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
aof-rewrite-incremental-fsync yes

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# Redis configuration file example
# Note on units: when memory size is needed, it is possible to specify
# it in the usual form of 1k 5GB 4M and so forth:
#
# 1k => 1000 bytes
# 1kb => 1024 bytes
# 1m => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# units are case insensitive so 1GB 1Gb 1gB are all the same.
################################## INCLUDES ###################################
# Include one or more other config files here. This is useful if you
# have a standard template that goes to all Redis server but also need
# to customize a few per-server settings. Include files can include
# other files, so use this wisely.
#
# Notice option "include" won't be rewritten by command "CONFIG REWRITE"
# from admin or Redis Sentinel. Since Redis always uses the last processed
# line as value of a configuration directive, you'd better put includes
# at the beginning of this file to avoid overwriting config change at runtime.
#
# If instead you are interested in using includes to override configuration
# options, it is better to use include as the last line.
#
# include /path/to/local.conf
# include /path/to/other.conf
################################ GENERAL #####################################
# By default Redis does not run as a daemon. Use 'yes' if you need it.
# Note that Redis will write a pid file in /var/run/redis.pid when daemonized.
daemonize no
# When running daemonized, Redis writes a pid file in /var/run/redis.pid by
# default. You can specify a custom pid file location here.
pidfile /var/run/redis.pid
# Accept connections on the specified port, default is 6379.
# If port 0 is specified Redis will not listen on a TCP socket.
port 6381
# TCP listen() backlog.
#
# In high requests-per-second environments you need an high backlog in order
# to avoid slow clients connections issues. Note that the Linux kernel
# will silently truncate it to the value of /proc/sys/net/core/somaxconn so
# make sure to raise both the value of somaxconn and tcp_max_syn_backlog
# in order to get the desired effect.
tcp-backlog 511
# By default Redis listens for connections from all the network interfaces
# available on the server. It is possible to listen to just one or multiple
# interfaces using the "bind" configuration directive, followed by one or
# more IP addresses.
#
# Examples:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1
# Specify the path for the Unix socket that will be used to listen for
# incoming connections. There is no default, so Redis will not listen
# on a unix socket when not specified.
#
unixsocket /tmp/redis.sock
unixsocketperm 755
# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
# TCP keepalive.
#
# If non-zero, use SO_KEEPALIVE to send TCP ACKs to clients in absence
# of communication. This is useful for two reasons:
#
# 1) Detect dead peers.
# 2) Take the connection alive from the point of view of network
# equipment in the middle.
#
# On Linux, the specified value (in seconds) is the period used to send ACKs.
# Note that to close the connection the double of the time is needed.
# On other kernels the period depends on the kernel configuration.
#
# A reasonable value for this option is 60 seconds.
tcp-keepalive 0
# Specify the server verbosity level.
# This can be one of:
# debug (a lot of information, useful for development/testing)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (moderately verbose, what you want in production probably)
# warning (only very important / critical messages are logged)
loglevel notice
# Specify the log file name. Also the empty string can be used to force
# Redis to log on the standard output. Note that if you use standard
# output for logging but daemonize, logs will be sent to /dev/null
logfile ""
# To enable logging to the system logger, just set 'syslog-enabled' to yes,
# and optionally update the other syslog parameters to suit your needs.
# syslog-enabled no
# Specify the syslog identity.
# syslog-ident redis
# Specify the syslog facility. Must be USER or between LOCAL0-LOCAL7.
# syslog-facility local0
# Set the number of databases. The default database is DB 0, you can select
# a different one on a per-connection basis using SELECT <dbid> where
# dbid is a number between 0 and 'databases'-1
databases 16
################################ SNAPSHOTTING ################################
#
# Save the DB on disk:
#
# save <seconds> <changes>
#
# Will save the DB if both the given number of seconds and the given
# number of write operations against the DB occurred.
#
# In the example below the behaviour will be to save:
# after 900 sec (15 min) if at least 1 key changed
# after 300 sec (5 min) if at least 10 keys changed
# after 60 sec if at least 10000 keys changed
#
# Note: you can disable saving at all commenting all the "save" lines.
#
# It is also possible to remove all the previously configured save
# points by adding a save directive with a single empty string argument
# like in the following example:
#
# save ""
#save 900 1
#save 300 10
#save 60 10000
# By default Redis will stop accepting writes if RDB snapshots are enabled
# (at least one save point) and the latest background save failed.
# This will make the user aware (in a hard way) that data is not persisting
# on disk properly, otherwise chances are that no one will notice and some
# disaster will happen.
#
# If the background saving process will start working again Redis will
# automatically allow writes again.
#
# However if you have setup your proper monitoring of the Redis server
# and persistence, you may want to disable this feature so that Redis will
# continue to work as usual even if there are problems with disk,
# permissions, and so forth.
stop-writes-on-bgsave-error yes
# Compress string objects using LZF when dump .rdb databases?
# For default that's set to 'yes' as it's almost always a win.
# If you want to save some CPU in the saving child set it to 'no' but
# the dataset will likely be bigger if you have compressible values or keys.
rdbcompression yes
# Since version 5 of RDB a CRC64 checksum is placed at the end of the file.
# This makes the format more resistant to corruption but there is a performance
# hit to pay (around 10%) when saving and loading RDB files, so you can disable it
# for maximum performances.
#
# RDB files created with checksum disabled have a checksum of zero that will
# tell the loading code to skip the check.
rdbchecksum yes
# The filename where to dump the DB
dbfilename dump3.rdb
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the 'dbfilename' configuration directive.
#
# The Append Only File will also be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir /home/user/dumps/
################################# REPLICATION #################################
# Master-Slave replication. Use slaveof to make a Redis instance a copy of
# another Redis server. Note that the configuration is local to the slave
# so for example it is possible to configure the slave to save the DB with a
# different interval, or to listen to another port, and so on.
#
# slaveof <masterip> <masterport>
# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the slave to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the slave request.
#
# masterauth <master-password>
# When a slave loses its connection with the master, or when the replication
# is still in progress, the slave can act in two different ways:
#
# 1) if slave-serve-stale-data is set to 'yes' (the default) the slave will
# still reply to client requests, possibly with out of date data, or the
# data set may just be empty if this is the first synchronization.
#
# 2) if slave-serve-stale-data is set to 'no' the slave will reply with
# an error "SYNC with master in progress" to all the kind of commands
# but to INFO and SLAVEOF.
#
slave-serve-stale-data yes
# You can configure a slave instance to accept writes or not. Writing against
# a slave instance may be useful to store some ephemeral data (because data
# written on a slave will be easily deleted after resync with the master) but
# may also cause problems if clients are writing to it because of a
# misconfiguration.
#
# Since Redis 2.6 by default slaves are read-only.
#
# Note: read only slaves are not designed to be exposed to untrusted clients
# on the internet. It's just a protection layer against misuse of the instance.
# Still a read only slave exports by default all the administrative commands
# such as CONFIG, DEBUG, and so forth. To a limited extent you can improve
# security of read only slaves using 'rename-command' to shadow all the
# administrative / dangerous commands.
slave-read-only yes
# Slaves send PINGs to server in a predefined interval. It's possible to change
# this interval with the repl_ping_slave_period option. The default value is 10
# seconds.
#
# repl-ping-slave-period 10
# The following option sets the replication timeout for:
#
# 1) Bulk transfer I/O during SYNC, from the point of view of slave.
# 2) Master timeout from the point of view of slaves (data, pings).
# 3) Slave timeout from the point of view of masters (REPLCONF ACK pings).
#
# It is important to make sure that this value is greater than the value
# specified for repl-ping-slave-period otherwise a timeout will be detected
# every time there is low traffic between the master and the slave.
#
# repl-timeout 60
# Disable TCP_NODELAY on the slave socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to slaves. But this can add a delay for
# the data to appear on the slave side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the slave side will
# be reduced but more bandwidth will be used for replication.
#
# By default we optimize for low latency, but in very high traffic conditions
# or when the master and slaves are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
# Set the replication backlog size. The backlog is a buffer that accumulates
# slave data when slaves are disconnected for some time, so that when a slave
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the slave missed while
# disconnected.
#
# The biggest the replication backlog, the longer the time the slave can be
# disconnected and later be able to perform a partial resynchronization.
#
# The backlog is only allocated once there is at least a slave connected.
#
# repl-backlog-size 1mb
# After a master has no longer connected slaves for some time, the backlog
# will be freed. The following option configures the amount of seconds that
# need to elapse, starting from the time the last slave disconnected, for
# the backlog buffer to be freed.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600
# The slave priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a slave to promote into a
# master if the master is no longer working correctly.
#
# A slave with a low priority number is considered better for promotion, so
# for instance if there are three slaves with priority 10, 100, 25 Sentinel will
# pick the one with priority 10, that is the lowest.
#
# However a special priority of 0 marks the slave as not able to perform the
# role of master, so a slave with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 100.
slave-priority 100
# It is possible for a master to stop accepting writes if there are less than
# N slaves connected, having a lag less or equal than M seconds.
#
# The N slaves need to be in "online" state.
#
# The lag in seconds, that must be <= the specified value, is calculated from
# the last ping received from the slave, that is usually sent every second.
#
# This option does not GUARANTEES that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough slaves
# are available, to the specified number of seconds.
#
# For example to require at least 3 slaves with a lag <= 10 seconds use:
#
# min-slaves-to-write 3
# min-slaves-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-slaves-to-write is set to 0 (feature disabled) and
# min-slaves-max-lag is set to 10.
################################## SECURITY ###################################
# Require clients to issue AUTH <PASSWORD> before processing any other
# commands. This might be useful in environments in which you do not trust
# others with access to the host running redis-server.
#
# This should stay commented out for backward compatibility and because most
# people do not need auth (e.g. they run their own servers).
#
# Warning: since Redis is pretty fast an outside user can try up to
# 150k passwords per second against a good box. This means that you should
# use a very strong password otherwise it will be very easy to break.
#
# requirepass foobared
# Command renaming.
#
# It is possible to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# hard to guess so that it will still be available for internal-use tools
# but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possible to completely kill a command by renaming it into
# an empty string:
#
# rename-command CONFIG ""
#
# Please note that changing the name of commands that are logged into the
# AOF file or transmitted to slaves may cause problems.
################################### LIMITS ####################################
# Set the max number of connected clients at the same time. By default
# this limit is set to 10000 clients, however if the Redis server is not
# able to configure the process file limit to allow for the specified limit
# the max number of allowed clients is set to the current file limit
# minus 32 (as Redis reserves a few file descriptors for internal uses).
#
# Once the limit is reached Redis will close all the new connections sending
# an error 'max number of clients reached'.
#
# maxclients 10000
# Don't use more memory than the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys
# according to the eviction policy selected (see maxmemory-policy).
#
# If Redis can't remove keys according to the policy, or if the policy is
# set to 'noeviction', Redis will start to reply with errors to commands
# that would use more memory, like SET, LPUSH, and so on, and will continue
# to reply to read-only commands like GET.
#
# This option is usually useful when using Redis as an LRU cache, or to set
# a hard memory limit for an instance (using the 'noeviction' policy).
#
# WARNING: If you have slaves attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the slaves are subtracted
# from the used memory count, so that network problems / resyncs will
# not trigger a loop where keys are evicted, and in turn the output
# buffer of slaves is full with DELs of keys evicted triggering the deletion
# of more keys, and so forth until the database is completely emptied.
#
# In short... if you have slaves attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for slave
# output buffers (but this is not needed if the policy is 'noeviction').
#
# maxmemory <bytes>
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# allkeys-lru -> remove any key accordingly to the LRU algorithm
# volatile-random -> remove a random key with an expire set
# allkeys-random -> remove a random key, any key
# volatile-ttl -> remove the key with the nearest expire time (minor TTL)
# noeviction -> don't expire at all, just return an error on write operations
#
# Note: with any of the above policies, Redis will return an error on write
# operations, when there are not suitable keys for eviction.
#
# At the date of writing this commands are: set setnx setex append
# incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
# sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
# zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
# getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy volatile-lru
# LRU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can select as well the sample
# size to check. For instance for default Redis will check three keys and
# pick the one that was used less recently, you can change the sample size
# using the following configuration directive.
#
# maxmemory-samples 3
############################## APPEND ONLY MODE ###############################
# By default Redis asynchronously dumps the dataset on disk. This mode is
# good enough in many applications, but an issue with the Redis process or
# a power outage may result into a few minutes of writes lost (depending on
# the configured save points).
#
# The Append Only File is an alternative persistence mode that provides
# much better durability. For instance using the default data fsync policy
# (see later in the config file) Redis can lose just one second of writes in a
# dramatic event like a server power outage, or a single write if something
# wrong with the Redis process itself happens, but the operating system is
# still running correctly.
#
# AOF and RDB persistence can be enabled at the same time without problems.
# If the AOF is enabled on startup Redis will load the AOF, that is the file
# with the better durability guarantees.
#
# Please check http://redis.io/topics/persistence for more information.
appendonly no
# The name of the append only file (default: "appendonly.aof")
appendfilename "appendonly.aof"
# The fsync() call tells the Operating System to actually write data on disk
# instead to wait for more data in the output buffer. Some OS will really flush
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log . Slow, Safest.
# everysec: fsync only one time every second. Compromise.
#
# The default is "everysec", as that's usually the right compromise between
# speed and data safety. It's up to you to understand if you can relax this to
# "no" that will let the operating system flush the output buffer when
# it wants, for better performances (but if you can live with the idea of
# some data loss consider the default persistence mode that's snapshotting),
# or on the contrary, use "always" that's very slow but a bit safer than
# everysec.
#
# More details please check the following article:
# http://antirez.com/post/redis-persistence-demystified.html
#
# If unsure, use "everysec".
# appendfsync always
appendfsync everysec
# appendfsync no
# When the AOF fsync policy is set to always or everysec, and a background
# saving process (a background save or AOF log background rewriting) is
# performing a lot of I/O against the disk, in some Linux configurations
# Redis may block too long on the fsync() call. Note that there is no fix for
# this currently, as even performing fsync in a different thread will block
# our synchronous write(2) call.
#
# In order to mitigate this problem it's possible to use the following option
# that will prevent fsync() from being called in the main process while a
# BGSAVE or BGREWRITEAOF is in progress.
#
# This means that while another child is saving, the durability of Redis is
# the same as "appendfsync none". In practical terms, this means that it is
# possible to lose up to 30 seconds of log in the worst scenario (with the
# default Linux settings).
#
# If you have latency problems turn this to "yes". Otherwise leave it as
# "no" that is the safest pick from the point of view of durability.
no-appendfsync-on-rewrite no
# Automatic rewrite of the append only file.
# Redis is able to automatically rewrite the log file implicitly calling
# BGREWRITEAOF when the AOF log size grows by the specified percentage.
#
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (if no rewrite has happened since the restart, the size of
# the AOF at startup is used).
#
# This base size is compared to the current size. If the current size is
# bigger than the specified percentage, the rewrite is triggered. Also
# you need to specify a minimal size for the AOF file to be rewritten, this
# is useful to avoid rewriting the AOF file even if the percentage increase
# is reached but it is still pretty small.
#
# Specify a percentage of zero in order to disable the automatic AOF
# rewrite feature.
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb
################################ LUA SCRIPTING ###############################
# Max execution time of a Lua script in milliseconds.
#
# If the maximum execution time is reached Redis will log that a script is
# still in execution after the maximum allowed time and will start to
# reply to queries with an error.
#
# When a long running script exceed the maximum execution time only the
# SCRIPT KILL and SHUTDOWN NOSAVE commands are available. The first can be
# used to stop a script that did not yet called write commands. The second
# is the only way to shut down the server in the case a write commands was
# already issue by the script but the user don't want to wait for the natural
# termination of the script.
#
# Set it to 0 or a negative value for unlimited execution without warnings.
lua-time-limit 5000
################################## SLOW LOG ###################################
# The Redis Slow Log is a system to log queries that exceeded a specified
# execution time. The execution time does not include the I/O operations
# like talking with the client, sending the reply and so forth,
# but just the time needed to actually execute the command (this is the only
# stage of command execution where the thread is blocked and can not serve
# other requests in the meantime).
#
# You can configure the slow log with two parameters: one tells Redis
# what is the execution time, in microseconds, to exceed in order for the
# command to get logged, and the other parameter is the length of the
# slow log. When a new command is logged the oldest one is removed from the
# queue of logged commands.
# The following time is expressed in microseconds, so 1000000 is equivalent
# to one second. Note that a negative number disables the slow log, while
# a value of zero forces the logging of every command.
slowlog-log-slower-than 10000
# There is no limit to this length. Just be aware that it will consume memory.
# You can reclaim memory used by the slow log with SLOWLOG RESET.
slowlog-max-len 128
############################# Event notification ##############################
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/keyspace-events
#
# For instance if keyspace events notification is enabled, and a client
# performs a DEL operation on key "foo" stored in the Database 0, two
# messages will be published via Pub/Sub:
#
# PUBLISH __keyspace@0__:foo del
# PUBLISH __keyevent@0__:del foo
#
# It is possible to select the events that Redis will notify among a set
# of classes. Every class is identified by a single character:
#
# K Keyspace events, published with __keyspace@<db>__ prefix.
# E Keyevent events, published with __keyevent@<db>__ prefix.
# g Generic commands (non-type specific) like DEL, EXPIRE, RENAME, ...
# $ String commands
# l List commands
# s Set commands
# h Hash commands
# z Sorted set commands
# x Expired events (events generated every time a key expires)
# e Evicted events (events generated when a key is evicted for maxmemory)
# A Alias for g$lshzxe, so that the "AKE" string means all the events.
#
# The "notify-keyspace-events" takes as argument a string that is composed
# by zero or multiple characters. The empty string means that notifications
# are disabled at all.
#
# Example: to enable list and generic events, from the point of view of the
# event name, use:
#
# notify-keyspace-events Elg
#
# Example 2: to get the stream of the expired keys subscribing to channel
# name __keyevent@0__:expired use:
#
# notify-keyspace-events Ex
#
# By default all notifications are disabled because most users don't need
# this feature and the feature has some overhead. Note that if you don't
# specify at least one of K or E, no events will be delivered.
notify-keyspace-events ""
############################### ADVANCED CONFIG ###############################
# Hashes are encoded using a memory efficient data structure when they have a
# small number of entries, and the biggest entry does not exceed a given
# threshold. These thresholds can be configured using the following directives.
hash-max-ziplist-entries 512
hash-max-ziplist-value 64
# Similarly to hashes, small lists are also encoded in a special way in order
# to save a lot of space. The special representation is only used when
# you are under the following limits:
list-max-ziplist-entries 512
list-max-ziplist-value 64
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happens to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512
# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64
# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
# order to help rehashing the main Redis hash table (the one mapping top-level
# keys to values). The hash table implementation Redis uses (see dict.c)
# performs a lazy rehashing: the more operation you run into a hash table
# that is rehashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
#
# The default is to use this millisecond 10 times every second in order to
# active rehashing the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply form time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes
# The client output buffer limits can be used to force disconnection of clients
# that are not reading data from the server fast enough for some reason (a
# common reason is that a Pub/Sub client can't consume messages as fast as the
# publisher can produce them).
#
# The limit can be set differently for the three different classes of clients:
#
# normal -> normal clients
# slave -> slave clients and MONITOR clients
# pubsub -> clients subscribed to at least one pubsub channel or pattern
#
# The syntax of every client-output-buffer-limit directive is the following:
#
# client-output-buffer-limit <class> <hard limit> <soft limit> <soft seconds>
#
# A client is immediately disconnected once the hard limit is reached, or if
# the soft limit is reached and remains reached for the specified number of
# seconds (continuously).
# So for instance if the hard limit is 32 megabytes and the soft limit is
# 16 megabytes / 10 seconds, the client will get disconnected immediately
# if the size of the output buffers reach 32 megabytes, but will also get
# disconnected if the client reaches 16 megabytes and continuously overcomes
# the limit for 10 seconds.
#
# By default normal clients are not limited because they don't receive data
# without asking (in a push way), but just after a request, so only
# asynchronous clients may create a scenario where data is requested faster
# than it can read.
#
# Instead there is a default limit for pubsub and slave clients, since
# subscribers and slaves receive data in a push fashion.
#
# Both the hard or the soft limit can be disabled by setting them to zero.
client-output-buffer-limit normal 0 0 0
client-output-buffer-limit slave 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
# Redis calls an internal function to perform many background tasks, like
# closing connections of clients in timeout, purging expired keys that are
# never requested, and so forth.
#
# Not all tasks are performed with the same frequency, but Redis checks for
# tasks to perform accordingly to the specified "hz" value.
#
# By default "hz" is set to 10. Raising the value will use more CPU when
# Redis is idle, but at the same time will make Redis more responsive when
# there are many keys expiring at the same time, and timeouts may be
# handled with more precision.
#
# The range is between 1 and 500, however a value over 100 is usually not
# a good idea. Most users should use the default of 10 and raise this up to
# 100 only in environments where very low latency is required.
hz 10
# When a child rewrites the AOF file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
aof-rewrite-incremental-fsync yes

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# -*- coding: utf-8 -*-
#
# AIL documentation build configuration file, created by
# sphinx-quickstart on Tue May 6 09:36:37 2014.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys, os
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
sys.path.insert(0, os.path.abspath('../../bin/'))
# -- General configuration -----------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.autodoc', 'sphinx.ext.intersphinx', 'sphinx.ext.ifconfig', 'sphinx.ext.viewcode']
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'AIL'
copyright = u'2014, Jules Debra and CIRCL - Computer Incident Response Center Luxembourg'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = '0.0.1'
# The full version, including alpha/beta/rc tags.
release = '0.0.1'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = []
# The reST default role (used for this markup: `text`) to use for all documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options for HTML output ---------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = 'default'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_domain_indices = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
#html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Output file base name for HTML help builder.
htmlhelp_basename = 'AILdoc'
# -- Options for LaTeX output --------------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#'preamble': '',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title, author, documentclass [howto/manual]).
latex_documents = [
('index', 'AIL.tex', u'AIL Documentation',
u'Jules Debra', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
#latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output --------------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('index', 'ail', u'AIL Documentation',
[u'Jules Debra'], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output ------------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'AIL', u'AIL Documentation',
u'Jules Debra', 'AIL', 'One line description of project.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# Example configuration for intersphinx: refer to the Python standard library.
intersphinx_mapping = {'http://docs.python.org/': None}

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.. AIL documentation master file, created by
sphinx-quickstart on Tue May 6 09:36:37 2014.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to AIL's documentation!
*******************************
.. toctree::
:maxdepth: 2
.. warning::
This is not the final version
lib_words
=========
.. automodule:: packages.lib_words
:members:
lib_gephi
=========
.. automodule:: packages.lib_gephi
:members:
lib_redis_insert
================
.. automodule:: packages.lib_redis_insert
:members:
lib_search
==========
.. automodule:: packages.lib_search
:members:
Paste
=====
.. automodule:: packages.Paste
:members:
ZMQ_PubSub
==========
.. automodule:: packages.ZMQ_PubSub
:members:
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

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mastercard
MA
visa
jcb
discover
americanexpress
amex
dankort
cogeban
banrisul
interac
discovercard
unionpay
CB
rupay
verve

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isFinite
isNaN
eval
var
parseFloat
javascript

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../files/mails_categ
../files/creditcard_categ
../files/pass_categ
../files/web_categ
../files/javascript_categ
../files/onion_categ

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gmail
hotmail
yahoo
orange
seznam
yandex
gmx
laposte
wanadoo
numericable
darty
bouygues
aol
outlook
hushmail
yandex
runbox
rediff
rackspace
mail
email
msn

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onion

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123456
password
12345678
qwerty
abc123
123456789
1234567
iloveyou
adobe123
123123
admin
1234567890
letmein
photoshop
1234
monkey
shadow
sunshine
12345
password1
princess
azerty
trustno1

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files/web_categ Normal file
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http
https
wwww

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password
oppetrol
bitcoin
opsavegaza
AnonGhost
Israel
Gaza
creditcard
tracker
compromise
malware
cert
flaw
exploit
0day
leak
database
terrorist
anonymous
opsyria
OpHackingCup
OpIsrael
OpBigBrother
dump
forex
vulnerable
phishing
account
stolen
wikileaks
gmail
hotmail
hackingteam
finfisher
gamma-international
COTTONMOUTH
COTTONMOUTH-I
COTTONMOUTH-II
COTTONMOUTH-III
DISHFIRE
TURMOIL
SCREAMINGHARPY
SECUREINSIGHT
SHAREDTAFFY
WAGONBED
WILLOWVIXEN

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#!/bin/bash
set -e
set -x
sudo apt-get update
sudo apt-get install python-pip
sudo apt-get install python-virtualenv
sudo apt-get install python-dev
sudo apt-get install libfreetype6-dev
virtualenv AILENV
. ./AILENV/bin/activate
pip install -r requirements.txt --upgrade
python -m textblob.download_corpora

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#Essential
redis
pyzmq
dnspython
#Graph
numpy
matplotlib
networkx
#Tokeniser
-U textblob
nltk
# Hashlib
crcmod
mmh3
#Others
python-magic
#optionnal
ipython
flask
texttable

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#!/usr/bin/env python2
# -*-coding:UTF-8 -*
import redis, ConfigParser, json
from datetime import date, datetime, time
from flask import Flask, request, render_template, jsonify
import flask
# CONFIG #
cfg = ConfigParser.ConfigParser()
cfg.read('../../bin/packages/config.cfg')
# REDIS #
r_serv = redis.StrictRedis(
host = cfg.get("Redis_Queues", "host"),
port = cfg.getint("Redis_Queues", "port"),
db = cfg.getint("Redis_Queues", "db"))
r_serv_log = redis.StrictRedis(
host = cfg.get("Redis_Log", "host"),
port = cfg.getint("Redis_Log", "port"),
db = cfg.getint("Redis_Log", "db"))
app = Flask(__name__, static_url_path='/static/')
def event_stream():
pubsub = r_serv_log.pubsub()
pubsub.psubscribe("Script" + '.*')
for msg in pubsub.listen():
level = msg['channel'].split('.')[1]
if msg['type'] == 'pmessage' and level != "DEBUG":
yield 'data: %s\n\n' % json.dumps(msg)
@app.route("/_logs")
def logs():
return flask.Response(event_stream(), mimetype="text/event-stream")
@app.route("/_stuff", methods = ['GET'])
def stuff():
row1 = []
for queue in r_serv.smembers("queues"):
row1.append((queue, r_serv.llen(queue)))
return jsonify(row1=row1)
@app.route("/")
def index():
row = []
for queue in r_serv.smembers("queues"):
row.append((queue, r_serv.llen(queue)))
return render_template("index.html", queues_name = row)
@app.route("/monitoring/")
def monitoring():
for queue in r_serv.smembers("queues"):
return render_template("Queue_live_Monitoring.html",last_value = queue)
@app.route("/wordstrending/")
def wordstrending():
return render_template("Wordstrending.html")
if __name__ == "__main__":
app.run(host='172.16.100.123' ,port=7000, threaded=True)

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#WordTrending .dygraph-legend > span { display: none; }
#WordTrending .dygraph-legend > span.highlight { display: inline; }
.dygraph-title { font-size: 42px; text-shadow: 2px 2px 2px gray; }
.dygraph-label { font-size: 18px; text-shadow: -2px 2px 2px gray; }

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function initfunc( csvay, scroot) {
window.csv = csvay;
window.scroot = scroot;
};
function update_values() {
//$SCRIPT_ROOT = {{request.script_root|tojson|safe}} ;
$SCRIPT_ROOT = window.scroot ;
$.getJSON($SCRIPT_ROOT+"/_stuff",
function(data) {
window.glob_tabvar = data;
});
};
var source = new EventSource('/_logs');
source.onmessage = function(event) {
var feed = jQuery.parseJSON( event.data );
create_log_table(feed);
};
function create_log_table(obj_json) {
tableBody = document.getElementById("tab_body")
var tr = document.createElement('TR')
var chan = document.createElement('TD')
var level = document.createElement('TD')
var scrpt = document.createElement('TD')
var src = document.createElement('TD')
var pdate = document.createElement('TD')
var nam = document.createElement('TD')
var msage = document.createElement('TD')
var chansplit = obj_json.channel.split('.');
var parsedmess = obj_json.data.split(';');
if( chansplit[1] == "INFO" ){
tr.className = "info";
}
else if ( chansplit[1] == "WARNING" ){
tr.className = "warning";
}
source_link = document.createElement("A");
if (parsedmess[1] == "slexy.org"){
soruce_url = "http://"+parsedmess[1]+"/view/"+parsedmess[3].split(".")[0];
}
else{
source_url = "http://"+parsedmess[1]+"/"+parsedmess[3].split(".")[0];
}
source_link.setAttribute("HREF",source_url);
source_link.setAttribute("TARGET", "_blank")
source_link.appendChild(document.createTextNode(parsedmess[1]));
src.appendChild(source_link);
chan.appendChild(document.createTextNode(chansplit[0]));
level.appendChild(document.createTextNode(chansplit[1]));
scrpt.appendChild(document.createTextNode(parsedmess[0]));
//src.appendChild(document.createTextNode(parsedmess[1]));
pdate.appendChild(document.createTextNode(parsedmess[2]));
nam.appendChild(document.createTextNode(parsedmess[3]));
msage.appendChild(document.createTextNode(parsedmess[4]));
tr.appendChild(chan);
tr.appendChild(level);
tr.appendChild(scrpt);
tr.appendChild(src);
tr.appendChild(pdate);
tr.appendChild(nam);
tr.appendChild(msage);
var sel = document.getElementById("log_select")
tableBody.appendChild(tr);
if (tableBody.rows.length > sel.options[sel.options.selectedIndex].value){
while (tableBody.rows.length != sel.options[sel.options.selectedIndex].value){
tableBody.deleteRow(0);
}
}
}
$(document).ready(function () {
var interval = 1000; //number of mili seconds between each call
var refresh = function() {
$.ajax({
url: "",
cache: false,
success: function(html) {
$('#server-name').html(html);
setTimeout(function() {
refresh();
update_values();
create_queue_table();
}, interval);
}
});
};
refresh();
});
function create_queue_table() {
document.getElementById("queueing").innerHTML = "";
var Tablediv = document.getElementById("queueing")
var table = document.createElement('TABLE')
table.className = "table table-bordered table-hover table-striped";
var tableHead = document.createElement('THEAD')
var tableBody = document.createElement('TBODY')
table.appendChild(tableHead);
table.appendChild(tableBody);
var heading = new Array();
heading[0] = "Queue Name"
heading[1] = "Amount"
var tr = document.createElement('TR');
tableHead.appendChild(tr);
for (i = 0; i < heading.length; i++) {
var th = document.createElement('TH')
th.width = '100';
th.appendChild(document.createTextNode(heading[i]));
tr.appendChild(th);
}
for(i = 0; i < (glob_tabvar.row1).length;i++){
var tr = document.createElement('TR')
for(j = 0; j < (glob_tabvar.row1[i]).length; j++){
var td = document.createElement('TD')
td.appendChild(document.createTextNode(glob_tabvar.row1[i][j]));
tr.appendChild(td)
}
tableBody.appendChild(tr);
}
Tablediv.appendChild(table);
}
$(document).ready(function () {
var data = [];
var x = new Date();
data.push([x, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]);
var g = new Dygraph(document.getElementById("Graph"), data,
{
labels: ["Time", "Duplicate", "CreditCard", "Words", "102", "Mails", "Lines", "Curve", "Onion", "Web", "Tokenize"],
drawPoints: false,
showRoller: true,
rollPeriod: 10,
labelsKMB: true,
logscale: true,
connectSeparatedPoints: true,
fillGraph: true,
stepPlot: true,
includeZero: true,
});
// It sucks that these things aren't objects, and we need to store state in window.
window.intervalId = setInterval(function() {
var x = new Date(); // current time
y = glob_tabvar.row1[0][1];
a = glob_tabvar.row1[1][1];
b = glob_tabvar.row1[2][1];
c = glob_tabvar.row1[3][1];
d = glob_tabvar.row1[4][1];
e = glob_tabvar.row1[5][1];
f = glob_tabvar.row1[6][1];
k = glob_tabvar.row1[7][1];
h = glob_tabvar.row1[8][1];
i = glob_tabvar.row1[9][1];
data.push([x, y, a, b, c, d, e, f, k, h, i]);
if (data.length > 1800) {
data.shift();
}
g.updateOptions( { 'file': data } );
}, 1000);
});

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<html>
<head>
<script type="text/javascript" src="{{ url_for('static', filename='js/dygraph-combined.js') }}"></script>
<script src="{{ url_for('static', filename='js/jquery-1.4.2.js') }}"></script>
</head>
<body>
<title>WordsTrend</title>
<script type="text/javascript">
$(document).ready(function () {
var data = [];
var t = new Date();
for (var i = 10; i >= 0; i--) {
var x = new Date(t.getTime() - i * 1000);
data.push([x, 0]);
}
var g = new Dygraph(document.getElementById("Graph"), data,
{
drawPoints: true,
showRoller: true,
//valueRange: [0.0, 1.2],
legend: 'always',
title: 'Pastes Queues Monitoring',
ylabel: 'Numbers of pastes waiting',
xlabel: 'Time',
});
// It sucks that these things aren't objects, and we need to store state in window.
window.intervalId = setInterval(function() {
var x = new Date(); // current time
var y = 6;
data.push([x, y]);
g.updateOptions( { 'file': data } );
}, 1000);
}
);
</script>
<div id="Graph" style="width:100%; height:100%;"></div>
</body>
</html>

209
var/www/templates/Wordstrending.html Normal file
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Analysis Information Leak framework Dashboard</title>
<!-- Core CSS -->
<link href="{{ url_for('static', filename='css/bootstrap.min.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='font-awesome-4.1.0/css/font-awesome.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='css/sb-admin-2.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='css/dygraph_gallery.css') }}" rel="stylesheet" type="text/css" />
<!-- JS -->
<script type="text/javascript" src="{{ url_for('static', filename='js/dygraph-combined.js') }}"></script>
<script src="{{ url_for('static', filename='js/jquery-1.4.2.js') }}"></script>
<script language="javascript" src="{{ url_for('static', filename='js/jquery.js')}}"></script>
</head>
<body>
<div id="wrapper">
<nav class="navbar navbar-default navbar-static-top" role="navigation" style="margin-bottom: 0">
<div class="navbar-header">
<a class="navbar-brand" href="{{ url_for('index') }}">Analysis Information Leak framework.</a>
</div>
<!-- /.navbar-top-links -->
<div class="navbar-default sidebar" role="navigation">
<div class="sidebar-collapse">
<ul class="nav" id="side-menu">
<li class="sidebar-search">
<div class="input-group custom-search-form">
<input type="text" class="form-control" placeholder="Search Paste">
<span class="input-group-btn">
<button class="btn btn-default" type="button">
<i class="fa fa-search"></i>
</button>
</span>
</div>
<!-- /input-group -->
</li>
<li>
<a href="{{ url_for('index') }}"><i class="fa fa-dashboard fa-fw"></i> Dashboard</a>
</li>
<li>
<a href="#"><i class="fa fa-bar-chart-o fa-fw"></i> Charts<span class="fa arrow"></span></a>
<ul class="nav nav-second-level">
<li>
<a href="{{ url_for('wordstrending') }}">WordsTrendings</a>
</li>
<li>
<a href="{{ url_for('monitoring') }}">Realtime_Queues</a>
</li>
</ul>
<!-- /.nav-second-level -->
</li>
</ul>
<!-- /#side-menu -->
</div>
<!-- /.sidebar-collapse -->
</div>
<!-- /.navbar-static-side -->
</nav>
<div id="page-wrapper">
<div class="row">
<div class="col-lg-12">
<h1 class="page-header">Wordtrending</h1>
</div>
<!-- /.col-lg-12 -->
</div>
<!-- /.row -->
<div class="row">
<div class="col-lg-12">
<div class="panel panel-default">
<div class="panel-heading">
<i class="fa fa-bar-chart-o fa-fw"></i> Words Trend
<div class="pull-right">
<div class="btn-group">
<button type="button" class="btn btn-default btn-xs dropdown-toggle" data-toggle="dropdown">
Actions
<span class="caret"></span>
</button>
<ul class="dropdown-menu pull-right" role="menu">
<li><a href="#" id="linear">Linear Scale</a>
</li>
<li><a href="#" id="log">Log Scale</a>
</li>
<li><a href="#" id="unzoom" onclick="unzoomGraph()">Unzoom</a>
</li>
<li class="divider"></li>
<li><a href="#" id="edit_graph">Edit graph words</a>
</li>
</ul>
</div>
</div>
</div>
<!-- /.panel-heading -->
<div class="panel-body">
<!-- <div id="WordTrending" style="width:100%;"></div> -->
<div id="WordTrending" style="width:100%; height:800px;"></div>
</div>
<!-- /.panel-body -->
</div>
</div>
<!-- /.row -->
</div>
<!-- /#page-wrapper -->
<script type="text/javascript">
g2 = new Dygraph(
document.getElementById("WordTrending"),
// path to CSV file
"{{ url_for('static', filename='csv/wordstrendingdata.csv') }}",
//"../csv/wordstrendingdata.csv",
//window.csv,
{
rollPeriod: 1,
showRoller: true,
//drawPoints: true,
//fillGraph: true,
logscale: true,
animatedZooms: true,
labelsKMB: true,
highlightCircleSize: 3,
highlightSeriesOpts: {
strokeWidth: 3,
strokeBorderWidth: 1,
highlightCircleSize: 5,
},
underlayCallback: function(canvas, area, g) {
canvas.fillStyle = "rgba(255, 193, 37, 0.5)";
function highlight_period(x_start, x_end) {
var canvas_left_x = g.toDomXCoord(x_start);
var canvas_right_x = g.toDomXCoord(x_end);
var canvas_width = canvas_right_x - canvas_left_x;
canvas.fillRect(canvas_left_x, area.y, canvas_width, area.h);
}
var min_data_x = g.getValue(0,0);
var max_data_x = g.getValue(g.numRows()-1,0);
// get day of week
var d = new Date(min_data_x);
var dow = d.getUTCDay();
var ds = d.toUTCString();
var w = min_data_x;
// starting on Sunday is a special case
if (dow == 0) {
highlight_period(w,w+12*3600*1000);
}
// find first saturday
while (dow != 5) {
w += 24*3600*1000;
d = new Date(w);
dow = d.getUTCDay();
}
// shift back 1/2 day to center highlight around the point for the day
w -= 12*3600*1000;
while (w < max_data_x) {
var start_x_highlight = w;
var end_x_highlight = w + 2*24*3600*1000;
// make sure we don't try to plot outside the graph
if (start_x_highlight < min_data_x) {
start_x_highlight = min_data_x;
}
if (end_x_highlight > max_data_x) {
end_x_highlight = max_data_x;
}
highlight_period(start_x_highlight,end_x_highlight);
// calculate start of highlight for next Saturday
w += 7*24*3600*1000;
}
}
});
onclick = function(ev) {
if (g2.isSeriesLocked()) {
g2.clearSelection();
}
else {
g2.setSelection(g2.getSelection(), g2.getHighlightSeries(), true);
}
};
g2.updateOptions({clickCallback: onclick}, true);
var linear = document.getElementById("linear");
var log = document.getElementById("log");
linear.onclick = function() { setLog(false); }
log.onclick = function() { setLog(true); }
var setLog = function(val) {
g2.updateOptions({ logscale: val });
linear.disabled = !val;
log.disabled = val;
}
function unzoomGraph() {
g2.updateOptions({
dateWindow:null,
valueRange:null
});
}
</script>
</div>
<script src="{{ url_for('static', filename='js/bootstrap.min.js') }}"></script>
</body>
</html>

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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Analysis Information Leak framework Dashboard</title>
<!-- Core CSS -->
<link href="{{ url_for('static', filename='css/bootstrap.min.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='font-awesome-4.1.0/css/font-awesome.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='css/sb-admin-2.css') }}" rel="stylesheet">
<link href="{{ url_for('static', filename='css/dygraph_gallery.css') }}" rel="stylesheet" type="text/css" />
<!-- JS -->
<script type="text/javascript" src="{{ url_for('static', filename='js/dygraph-combined.js') }}"></script>
<script src="{{ url_for('static', filename='js/jquery.js') }}"></script>
<script src="{{ url_for('static', filename='js/jquery-1.4.2.js') }}"></script>
</head>
<body>
<div id="wrapper">
<nav class="navbar navbar-default navbar-static-top" role="navigation" style="margin-bottom: 0">
<div class="navbar-header">
<a class="navbar-brand" href="{{ url_for('index') }}">Analysis Information Leak framework.</a>
</div>
<!-- /.navbar-top-links -->
<div class="navbar-default sidebar" role="navigation">
<div class="sidebar-collapse">
<ul class="nav" id="side-menu">
<li class="sidebar-search">
<div class="input-group custom-search-form">
<input type="text" class="form-control" placeholder="Search Paste">
<span class="input-group-btn">
<button class="btn btn-default" type="button">
<i class="fa fa-search"></i>
</button>
</span>
</div>
<!-- /input-group -->
</li>
<li>
<a href="{{ url_for('index') }}"><i class="fa fa-dashboard fa-fw"></i> Dashboard</a>
</li>
<li>
<a href="#"><i class="fa fa-bar-chart-o fa-fw"></i> Charts<span class="fa arrow"></span></a>
<ul class="nav nav-second-level">
<li>
<a href="{{ url_for('wordstrending') }}">WordsTrendings</a>
</li>
</ul>
<!-- /.nav-second-level -->
</li>
</ul>
<!-- /#side-menu -->
</div>
<!-- /.sidebar-collapse -->
</div>
<!-- /.navbar-static-side -->
</nav>
<div id="page-wrapper">
<div class="row">
<div class="col-lg-12">
<h1 class="page-header">Dashboard</h1>
</div>
<!-- /.col-lg-12 -->
</div>
<!-- /.row -->
<div class="row">
<div class="col-lg-12">
<div class="panel panel-default">
<div class="panel-heading">
<i class="fa fa-bar-chart-o fa-fw"></i> Queues Monitor
</div>
<div class="panel-body">
<div class="row">
<div class="col-lg-2">
<div class="table-responsive", id="queueing"></div>
</div>
<div class="col-lg-10" id="Graph" style="height:450px; width:80%;"></div>
</div>
<!-- /.row -->
</div>
<!-- /.panel-body -->
</div>
<!-- /.panel -->
</div>
<!-- /.col-lg-8 -->
<div class="col-lg-12">
<div class="panel panel-default">
<div class="panel-heading">
<i class="fa fa-tasks fa-fw"></i> Logs
</div>
<div class="panel-body">
<div class="table-responsive", id="logger">
<div class="row">
<div class="col-sm-6">
<div id="dataTables-example_length" class="dataTables_length">
<label>
<select class="form-control input-sm" name="dataTables-example_length" aria-controls="dataTables-example" id="log_select">
<option value="10">10</option>
<option value="25">25</option>
<option value="50">50</option>
<option value="100">100</option>
</select>
</label>
</div>
</div>
</div>
<table class="table table-bordered table-hover table-striped" id="table_log">
<thead>
<tr>
<th>Channel</th>
<th>Level</th>
<th>Script Name</th>
<th>Source</th>
<th>Date</th>
<th>Paste name</th>
<th>Message</th>
</tr>
</thead>
<tbody id="tab_body">
</tbody>
<table>
</div>
</div>
</div>
</div>
<!-- /.row -->
</div>
<!-- /#page-wrapper -->
</div>
<script type="text/javascript" src="{{ url_for('static', filename='js/indexjavascript.js')}}"></script>
<script type="text/javascript">
initfunc( "{{ url_for('static', filename='csv/wordstrendingdata.csv') }}", {{ request.script_root|tojson|safe }} );
</script>
<script src="{{ url_for('static', filename='js/jquery.js') }}"></script>
<script src="{{ url_for('static', filename='js/bootstrap.min.js') }}"></script>
<script src="{{ url_for('static', filename='js/plugins/metisMenu/metisMenu.js') }}"></script>
</body>
</html>

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var/www/update_thirdparty.sh Executable file
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#!/bin/bash
set -e
wget http://dygraphs.com/dygraph-combined.js -O ./static/js/dygraph-combined.js
SBADMIN_VERSION=2
filename="sb-admin-${SBADMIN_VERSION}"
rm -rf temp
mkdir temp
wget http://startbootstrap.com/downloads/${filename}".zip" -O temp/${filename}".zip"
unzip temp/${filename}".zip" -d temp/
JQVERSION="1.11.1"
wget http://code.jquery.com/jquery-${JQVERSION}.js -O ./static/js/jquery.js
wget https://collabdev.googlecode.com/svn-history/r5/trunk/static/js/jquery.timers-1.0.0.js -O ./static/js/jquery.timers-1.0.0.js
#Here to fix an error about an hard dependency in a obscur script of bootstrap..
wget http://code.jquery.com/jquery-1.4.2.js -O ./static/js/jquery-1.4.2.js
rm -rf ./static/js/plugins
mv temp/${filename}/js/* ./static/js/
rm -rf ./static/fonts/ ./static/font-awesome-4.1.0/
mv temp/${filename}/fonts/ ./static/
mv temp/${filename}/font-awesome-4.1.0/ ./static/
rm -rf ./static/css/plugins/
mv temp/${filename}/css/* ./static/css/
rm -rf temp/