mirror of
https://github.com/sqlmapproject/sqlmap.git
synced 2025-11-04 01:47:37 +03:00
133 lines
5.5 KiB
Python
133 lines
5.5 KiB
Python
######################## BEGIN LICENSE BLOCK ########################
|
|
# The Original Code is Mozilla Universal charset detector code.
|
|
#
|
|
# The Initial Developer of the Original Code is
|
|
# Netscape Communications Corporation.
|
|
# Portions created by the Initial Developer are Copyright (C) 2001
|
|
# the Initial Developer. All Rights Reserved.
|
|
#
|
|
# Contributor(s):
|
|
# Mark Pilgrim - port to Python
|
|
# Shy Shalom - original C code
|
|
#
|
|
# This library is free software; you can redistribute it and/or
|
|
# modify it under the terms of the GNU Lesser General Public
|
|
# License as published by the Free Software Foundation; either
|
|
# version 2.1 of the License, or (at your option) any later version.
|
|
#
|
|
# This library 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
|
|
# Lesser General Public License for more details.
|
|
#
|
|
# You should have received a copy of the GNU Lesser General Public
|
|
# License along with this library; if not, write to the Free Software
|
|
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
|
|
# 02110-1301 USA
|
|
######################### END LICENSE BLOCK #########################
|
|
|
|
from .charsetprober import CharSetProber
|
|
from .enums import CharacterCategory, ProbingState, SequenceLikelihood
|
|
|
|
|
|
class SingleByteCharSetProber(CharSetProber):
|
|
SAMPLE_SIZE = 64
|
|
SB_ENOUGH_REL_THRESHOLD = 1024 # 0.25 * SAMPLE_SIZE^2
|
|
POSITIVE_SHORTCUT_THRESHOLD = 0.95
|
|
NEGATIVE_SHORTCUT_THRESHOLD = 0.05
|
|
|
|
def __init__(self, model, reversed=False, name_prober=None):
|
|
super(SingleByteCharSetProber, self).__init__()
|
|
self._model = model
|
|
# TRUE if we need to reverse every pair in the model lookup
|
|
self._reversed = reversed
|
|
# Optional auxiliary prober for name decision
|
|
self._name_prober = name_prober
|
|
self._last_order = None
|
|
self._seq_counters = None
|
|
self._total_seqs = None
|
|
self._total_char = None
|
|
self._freq_char = None
|
|
self.reset()
|
|
|
|
def reset(self):
|
|
super(SingleByteCharSetProber, self).reset()
|
|
# char order of last character
|
|
self._last_order = 255
|
|
self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
|
|
self._total_seqs = 0
|
|
self._total_char = 0
|
|
# characters that fall in our sampling range
|
|
self._freq_char = 0
|
|
|
|
@property
|
|
def charset_name(self):
|
|
if self._name_prober:
|
|
return self._name_prober.charset_name
|
|
else:
|
|
return self._model['charset_name']
|
|
|
|
@property
|
|
def language(self):
|
|
if self._name_prober:
|
|
return self._name_prober.language
|
|
else:
|
|
return self._model.get('language')
|
|
|
|
def feed(self, byte_str):
|
|
if not self._model['keep_english_letter']:
|
|
byte_str = self.filter_international_words(byte_str)
|
|
if not byte_str:
|
|
return self.state
|
|
char_to_order_map = self._model['char_to_order_map']
|
|
for i, c in enumerate(byte_str):
|
|
# XXX: Order is in range 1-64, so one would think we want 0-63 here,
|
|
# but that leads to 27 more test failures than before.
|
|
order = char_to_order_map[c]
|
|
# XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
|
|
# CharacterCategory.SYMBOL is actually 253, so we use CONTROL
|
|
# to make it closer to the original intent. The only difference
|
|
# is whether or not we count digits and control characters for
|
|
# _total_char purposes.
|
|
if order < CharacterCategory.CONTROL:
|
|
self._total_char += 1
|
|
if order < self.SAMPLE_SIZE:
|
|
self._freq_char += 1
|
|
if self._last_order < self.SAMPLE_SIZE:
|
|
self._total_seqs += 1
|
|
if not self._reversed:
|
|
i = (self._last_order * self.SAMPLE_SIZE) + order
|
|
model = self._model['precedence_matrix'][i]
|
|
else: # reverse the order of the letters in the lookup
|
|
i = (order * self.SAMPLE_SIZE) + self._last_order
|
|
model = self._model['precedence_matrix'][i]
|
|
self._seq_counters[model] += 1
|
|
self._last_order = order
|
|
|
|
charset_name = self._model['charset_name']
|
|
if self.state == ProbingState.DETECTING:
|
|
if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
|
|
confidence = self.get_confidence()
|
|
if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
|
|
self.logger.debug('%s confidence = %s, we have a winner',
|
|
charset_name, confidence)
|
|
self._state = ProbingState.FOUND_IT
|
|
elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
|
|
self.logger.debug('%s confidence = %s, below negative '
|
|
'shortcut threshhold %s', charset_name,
|
|
confidence,
|
|
self.NEGATIVE_SHORTCUT_THRESHOLD)
|
|
self._state = ProbingState.NOT_ME
|
|
|
|
return self.state
|
|
|
|
def get_confidence(self):
|
|
r = 0.01
|
|
if self._total_seqs > 0:
|
|
r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) /
|
|
self._total_seqs / self._model['typical_positive_ratio'])
|
|
r = r * self._freq_char / self._total_char
|
|
if r >= 1.0:
|
|
r = 0.99
|
|
return r
|