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#!/usr/bin/env python3
# Autodict-QL - Optimal token generation for fuzzing
# Part of AFL++ Project
# Author : Microsvuln - Arash.vre@gmail.com
import os
import string
import binascii
import codecs
import errno
import struct
import argparse
import re
from binascii import unhexlify
def ensure_dir(dir):
try:
os.makedirs(dir)
except OSError as e:
if e.errno != errno.EEXIST:
raise
def parse_args():
parser = argparse.ArgumentParser(description=(
"Helper - Specify input file analysis and output folder to save corpus for strings in the overall project --------------------------------------------------------------------------- Example usage : python2 thisfile.py outdir str.txt" ))
parser.add_argument("corpdir",
help="The path to the corpus directory to generate strings.")
parser.add_argument("infile",
help="Specify file output of codeql analysis - ex. ooo-atr.txt, analysis take place on this file, example : python2 thisfile.py outdir strings.txt")
return parser.parse_args()
def do_string_analysis(corpdir, infile1):
with open(infile1, "r") as f1:
lines = f1.readlines()[1:]
f1.close()
new_lst1 = []
n = 1
for i, num1 in enumerate(lines):
if i != 0:
new_lst1.append(num1)
#print("num : %s" % num1)
str11 = str(num1)
str11 = str11.replace("|","")
str11 = str11.replace("\n","")
str11 = str11.lstrip()
str11 = str11.rstrip()
str11 = str(str11)
if ((" " in str11 ) or (")" in str11) or ("(" in str11) or ("<" in str11) or (">" in str11)) :
print("Space / Paranthesis String : %s" % str11)
else :
with open(corpdir+'/memcmp-str{0}'.format(n), 'w') as file:
file.write(str11)
print("AFL++ Autodict-QL by Microsvuln : Writing Token : %s" % str11)
n=n+1
def main():
args = parse_args()
ensure_dir(args.corpdir)
do_string_analysis(args.corpdir, args.infile)
if __name__ == '__main__':
main()
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