Implemented optimal mask generation logic.
Removed obsolete psyco module.
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iphelix
parent
4f84adc320
commit
b1958e6cdb
260
maskgen.py
260
maskgen.py
@ -28,120 +28,104 @@
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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import csv, string
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import sys
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import csv
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import datetime
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from operator import itemgetter
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from optparse import OptionParser
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import code
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VERSION = "0.0.2"
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# PPS (Passwords per Second) Cracking Speed
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pps = 1000000000
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# Global Variables
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mastermasks = dict()
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allmasks = dict()
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class MaskGen:
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def __init__(self):
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# Masks collections with meta data
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self.masks = dict()
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self.lengthmasks = dict()
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##################################################################
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## Calculate complexity of a single mask
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##################################################################
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def complexity(mask):
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count = 1
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for char in mask[1:].split("?"):
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self.minlength = 0
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self.maxlength = sys.maxint
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# Loweralpha
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if char == "l":
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count *= 26
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self.maxtime = sys.maxint
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# Upperalpha
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elif char == "u":
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count *= 26
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self.complexity = sys.maxint
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self.occurrence = 0
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# Numeric
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elif char == "d":
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count *= 10
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# PPS (Passwords per Second) Cracking Speed
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self.pps = 1000000000
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# Special
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elif char == "s":
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count *= 33
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self.checkmask = False
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self.showmasks = False
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# Unknown mask
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else:
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print "[!] Error, unknown mask ?%s in a mask %s" % (char,mask)
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# Counter for total masks coverage
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self.total_occurrence = 0
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return count
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def getcomplexity(self, mask):
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""" Return mask complexity. """
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count = 1
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for char in mask[1:].split("?"):
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if char == "l": count *= 26
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elif char == "u": count *= 26
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elif char == "d": count *= 10
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elif char == "s": count *= 33
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else: print "[!] Error, unknown mask ?%s in a mask %s" % (char,mask)
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###################################################################
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## Calculate complexity of a complex mask
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###################################################################
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def maskcomplexity(mask):
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combined_complexity = 1
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for submask in mask.split():
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combined_complexity *= complexity(submask)
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return count
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return combined_complexity
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def loadmasks(self, filename):
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""" Load masks and apply filters. """
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maskReader = csv.reader(open(args[0],'r'), delimiter=',', quotechar='"')
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###################################################################
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## Check if complex mask matches a sample mask
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###################################################################
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def matchmask(checkmask,mask):
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length = len(mask)/2
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checklength = len(checkmask.split(" "))
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for (mask,occurrence) in maskReader:
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if length == checklength:
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masklist = mask[1:].split("?")
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for i, submask in enumerate(checkmask.split(" ")):
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for char in submask[1:].split("?"):
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if char == masklist[i]:
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break
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else:
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return False
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else:
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return True
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else:
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return False
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mask_occurrence = int(occurrence)
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mask_length = len(mask)/2
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mask_complexity = self.getcomplexity(mask)
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self.total_occurrence =+ mask_occurrence
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# Apply filters based on occurrence, length, complexity and time
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if mask_occurrence >= self.occurrence and \
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mask_complexity <= self.complexity and \
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mask_length <= self.maxlength and \
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mask_length >= self.minlength:
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###################################################################
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## Combine masks
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###################################################################
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def genmask(mask):
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global mastermasks
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length = len(mask)/2
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if not length in mastermasks:
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mastermasks[length] = dict()
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for i,v in enumerate(mask[1:].split("?")):
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self.masks[mask] = dict()
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self.masks[mask]['length'] = mask_length
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self.masks[mask]['occurrence'] = mask_occurrence
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self.masks[mask]['complexity'] = mask_complexity
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self.masks[mask]['time'] = mask_complexity/self.pps
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self.masks[mask]['optindex'] = mask_complexity/mask_occurrence
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if not i in mastermasks[length]:
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mastermasks[length][i] = set()
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def print_optimal_index_masks(self):
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print "[*] Masks sorted by optimal index."
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mastermasks[length][i].add("?%s" % v)
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sample_time = 0
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sample_occurrence = 0
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###################################################################
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## Store all masks in based on length and count
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###################################################################
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def storemask(mask,occurrence):
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global allmasks
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length = len(mask)/2
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if not length in allmasks:
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allmasks[length] = dict()
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allmasks[length][mask] = int(occurrence)
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# TODO Group by time here 1 minutes, 1 hour, 1 day, 1 month, 1 year....
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# Group by length 1,2,3,4,5,6,7,8,9,10....
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# Group by occurrence 10%, 20%, 30%, 40%, 50%....
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def main():
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# Constants
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total_occurrence = 0
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sample_occurrence = 0
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sample_time = 0
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for mask in sorted(self.masks.keys(), key=lambda mask: self.masks[mask]['optindex'], reverse=False):
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# TODO: I want to actually see statistical analysis of masks not just based on size but also frequency and time
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# per length and per count
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time_human = "EXCEEDED" if self.masks[mask]['time'] > 60*60*24 else str(datetime.timedelta(seconds=self.masks[mask]['time']))
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print "[{:<2}] {:<30} [{:>8}] [{:>7}] ".format(self.masks[mask]['length'], mask, time_human, self.masks[mask]['occurrence'])
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sample_occurrence =+ self.masks[mask]['occurrence']
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sample_time =+ self.masks[mask]['time']
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if sample_time > self.maxtime:
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print "[!] Estimated runtime exceeded."
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break
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print "[*] Coverage is %d%% (%d/%d)" % (sample_occurrence*100/self.total_occurrence,sample_occurrence,self.total_occurrence)
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#print "[*] Total time [%dd|%dh|%dm|%ds]" % (sample_time/60/60/24,sample_time/60/60,sample_time/60,sample_time)
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if __name__ == "__main__":
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header = " _ \n"
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header += " MaskGen 0.0.2 | |\n"
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header += " MaskGen %s | |\n" % VERSION
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header += " _ __ __ _ ___| | _\n"
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header += " | '_ \ / _` |/ __| |/ /\n"
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header += " | |_) | (_| | (__| < \n"
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@ -151,109 +135,53 @@ def main():
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header += "\n"
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parser = OptionParser("%prog [options] masksfile.csv", version="%prog "+VERSION)
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parser.add_option("--minlength", dest="minlength",help="Minimum password length", type="int", metavar="8")
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parser.add_option("--maxlength", dest="maxlength",help="Maximum password length", type="int", metavar="8")
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parser.add_option("--mintime", dest="mintime",help="Minimum time to crack", type="int", metavar="")
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parser.add_option("--maxtime", dest="maxtime",help="Maximum time to crack", type="int", metavar="")
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parser.add_option("--maxtime", dest="maxtime",help="Maximum total time (optimized)", type="int", metavar="")
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parser.add_option("--complexity", dest="complexity",help="maximum password complexity", type="int", metavar="")
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parser.add_option("--occurrence", dest="occurrence",help="minimum times mask was used", type="int", metavar="")
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parser.add_option("--checkmask", dest="checkmask",help="check mask coverage", metavar="?u?l ?l ?l ?l ?l ?d")
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parser.add_option("--showmasks", dest="showmasks",help="Show matching masks", action="store_true", default=False)
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parser.add_option("--pps", dest="pps",help="Passwords per Second", type="int", default=pps, metavar="1000000000")
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parser.add_option("--pps", dest="pps",help="Passwords per Second", type="int", metavar="1000000000")
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parser.add_option("-o", "--masksoutput", dest="masks_output",help="Save masks to a file", metavar="masks.hcmask")
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parser.add_option("-q", "--quiet", action="store_true", dest="quiet", default=False, help="Don't show headers.")
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(options, args) = parser.parse_args()
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# Print program header
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if not options.quiet:
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if not options.quiet:
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print header
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if len(args) != 1:
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parser.error("no masks file specified")
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exit(1)
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# Constants
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total_occurrence = 0
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sample_occurrence = 0
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sample_time = 0
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print "[*] Analysing masks: %s" % args[0]
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maskReader = csv.reader(open(args[0],'r'), delimiter=',', quotechar='"')
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#headerline = maskReader.next()
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# Check the coverage of a particular mask for a given set
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if options.checkmask:
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length = len(options.checkmask.split(" "))
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maskgen = MaskGen()
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# Prepare master mask list for analysis
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mastermasks[length] = dict()
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if options.minlength: maskgen.minlength = options.minlength
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if options.maxlength: maskgen.maxlength = options.maxlength
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for i, submask in enumerate(options.checkmask.split(" ")):
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if options.maxtime: maskgen.maxtime = options.maxtime
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mastermasks[length][i] = set()
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for char in submask[1:].split("?"):
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mastermasks[length][i].add("?%s" % char)
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if options.complexity: maskgen.complexity = options.complexity
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if options.occurrence: maskgen.occurrence = options.occurrence
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for (mask,occurrence) in maskReader:
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total_occurrence += int(occurrence)
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if matchmask(options.checkmask,mask):
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sample_occurrence += int(occurrence)
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storemask(mask,occurrence)
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if options.pps: maskgen.pps = options.pps
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if options.checkmask: maskgen.checkmask = options.checkmask
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if options.showmasks: maskgen.showmasks = options.showmask
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# Generate masks from a given set
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else:
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for (mask,occurrence) in maskReader:
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total_occurrence += int(occurrence)
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if (not options.occurrence or int(occurrence) >= options.occurrence) and \
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(not options.maxlength or len(mask)/2 <= options.maxlength) and \
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(not options.minlength or len(mask)/2 >= options.minlength) and \
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(not options.complexity or complexity(mask) <= options.complexity) and \
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(not options.maxtime or complexity(mask)/options.pps <= options.maxtime) and \
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(not options.mintime or complexity(mask)/options.pps >= options.mintime):
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genmask(mask)
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storemask(mask,occurrence)
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sample_occurrence += int(occurrence)
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####################################################################################
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## Analysis
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####################################################################################
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if options.masks_output:
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f = open(options.masks_output,'w+')
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for length,lengthmask in sorted(mastermasks.iteritems()):
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maskstring = ""
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for position,maskset in lengthmask.iteritems():
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maskstring += "%s " % string.join(maskset,"")
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# Load masks
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maskgen.loadmasks(args[0])
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maskgen.print_optimal_index_masks()
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length_occurrence = 0
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combined_mask_time = 0
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# Calculate occurrence and time complexity of component masks
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# for each password length.
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for mask, occurrence in allmasks[length].iteritems():
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length_occurrence += int(occurrence)
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combined_mask_time += complexity(mask)/options.pps
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sample_time += combined_mask_time
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time_string = "Don't bother."
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if not combined_mask_time > 3784320000:
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time_string = str(datetime.timedelta(seconds=combined_mask_time))
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print "[*] [%d] [%d/%d] [%.02f] [%s]" % (length, length_occurrence, total_occurrence, length_occurrence*100/total_occurrence, time_string)
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if options.showmasks:
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for mask,mask_occurrence in sorted(allmasks[length].iteritems(),key=itemgetter(1),reverse=True):
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mask_time = complexity(mask)/options.pps
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print " [%d] [%d/%d] [%.02f] [%.02f] [%dd|%dh|%dm|%ds] %s" % (length, mask_occurrence, length_occurrence, mask_occurrence*100/length_occurrence, mask_occurrence*100/total_occurrence,mask_time/60/60/24, mask_time/60/60, mask_time/60, mask_time,mask)
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if options.masks_output:
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for mask,mask_occurrence in sorted(allmasks[length].iteritems(),key=itemgetter(1),reverse=True):
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f.write("%s\n" % mask)
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print "[*] Coverage is %%%d (%d/%d)" % (sample_occurrence*100/total_occurrence,sample_occurrence,total_occurrence)
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print "[*] Total time [%dd|%dh|%dm|%ds]" % (sample_time/60/60/24,sample_time/60/60,sample_time/60,sample_time)
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if __name__ == "__main__":
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main()
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@ -34,13 +34,6 @@ from optparse import OptionParser
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VERSION = "0.0.2"
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try:
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import psyco
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psyco.full()
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print "[*] Using Psyco to accelerate parsing."
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except ImportError:
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print "[?] Psyco is not available. Install Psyco on 32-bit systems for faster parsing."
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password_counter = 0
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# Constants
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