mirror of
https://github.com/sqlmapproject/sqlmap.git
synced 2025-10-31 16:07:55 +03:00
270 lines
13 KiB
Python
Executable File
270 lines
13 KiB
Python
Executable File
######################## BEGIN LICENSE BLOCK ########################
|
|
# The Original Code is Mozilla Universal charset detector code.
|
|
#
|
|
# The Initial Developer of the Original Code is
|
|
# Shy Shalom
|
|
# Portions created by the Initial Developer are Copyright (C) 2005
|
|
# the Initial Developer. All Rights Reserved.
|
|
#
|
|
# Contributor(s):
|
|
# Mark Pilgrim - port to Python
|
|
#
|
|
# 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
|
|
import constants
|
|
|
|
# This prober doesn't actually recognize a language or a charset.
|
|
# It is a helper prober for the use of the Hebrew model probers
|
|
|
|
### General ideas of the Hebrew charset recognition ###
|
|
#
|
|
# Four main charsets exist in Hebrew:
|
|
# "ISO-8859-8" - Visual Hebrew
|
|
# "windows-1255" - Logical Hebrew
|
|
# "ISO-8859-8-I" - Logical Hebrew
|
|
# "x-mac-hebrew" - ?? Logical Hebrew ??
|
|
#
|
|
# Both "ISO" charsets use a completely identical set of code points, whereas
|
|
# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
|
|
# these code points. windows-1255 defines additional characters in the range
|
|
# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
|
|
# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
|
|
# x-mac-hebrew defines similar additional code points but with a different
|
|
# mapping.
|
|
#
|
|
# As far as an average Hebrew text with no diacritics is concerned, all four
|
|
# charsets are identical with respect to code points. Meaning that for the
|
|
# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
|
|
# (including final letters).
|
|
#
|
|
# The dominant difference between these charsets is their directionality.
|
|
# "Visual" directionality means that the text is ordered as if the renderer is
|
|
# not aware of a BIDI rendering algorithm. The renderer sees the text and
|
|
# draws it from left to right. The text itself when ordered naturally is read
|
|
# backwards. A buffer of Visual Hebrew generally looks like so:
|
|
# "[last word of first line spelled backwards] [whole line ordered backwards
|
|
# and spelled backwards] [first word of first line spelled backwards]
|
|
# [end of line] [last word of second line] ... etc' "
|
|
# adding punctuation marks, numbers and English text to visual text is
|
|
# naturally also "visual" and from left to right.
|
|
#
|
|
# "Logical" directionality means the text is ordered "naturally" according to
|
|
# the order it is read. It is the responsibility of the renderer to display
|
|
# the text from right to left. A BIDI algorithm is used to place general
|
|
# punctuation marks, numbers and English text in the text.
|
|
#
|
|
# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
|
|
# what little evidence I could find, it seems that its general directionality
|
|
# is Logical.
|
|
#
|
|
# To sum up all of the above, the Hebrew probing mechanism knows about two
|
|
# charsets:
|
|
# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
|
|
# backwards while line order is natural. For charset recognition purposes
|
|
# the line order is unimportant (In fact, for this implementation, even
|
|
# word order is unimportant).
|
|
# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
|
|
#
|
|
# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
|
|
# specifically identified.
|
|
# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
|
|
# that contain special punctuation marks or diacritics is displayed with
|
|
# some unconverted characters showing as question marks. This problem might
|
|
# be corrected using another model prober for x-mac-hebrew. Due to the fact
|
|
# that x-mac-hebrew texts are so rare, writing another model prober isn't
|
|
# worth the effort and performance hit.
|
|
#
|
|
#### The Prober ####
|
|
#
|
|
# The prober is divided between two SBCharSetProbers and a HebrewProber,
|
|
# all of which are managed, created, fed data, inquired and deleted by the
|
|
# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
|
|
# fact some kind of Hebrew, Logical or Visual. The final decision about which
|
|
# one is it is made by the HebrewProber by combining final-letter scores
|
|
# with the scores of the two SBCharSetProbers to produce a final answer.
|
|
#
|
|
# The SBCSGroupProber is responsible for stripping the original text of HTML
|
|
# tags, English characters, numbers, low-ASCII punctuation characters, spaces
|
|
# and new lines. It reduces any sequence of such characters to a single space.
|
|
# The buffer fed to each prober in the SBCS group prober is pure text in
|
|
# high-ASCII.
|
|
# The two SBCharSetProbers (model probers) share the same language model:
|
|
# Win1255Model.
|
|
# The first SBCharSetProber uses the model normally as any other
|
|
# SBCharSetProber does, to recognize windows-1255, upon which this model was
|
|
# built. The second SBCharSetProber is told to make the pair-of-letter
|
|
# lookup in the language model backwards. This in practice exactly simulates
|
|
# a visual Hebrew model using the windows-1255 logical Hebrew model.
|
|
#
|
|
# The HebrewProber is not using any language model. All it does is look for
|
|
# final-letter evidence suggesting the text is either logical Hebrew or visual
|
|
# Hebrew. Disjointed from the model probers, the results of the HebrewProber
|
|
# alone are meaningless. HebrewProber always returns 0.00 as confidence
|
|
# since it never identifies a charset by itself. Instead, the pointer to the
|
|
# HebrewProber is passed to the model probers as a helper "Name Prober".
|
|
# When the Group prober receives a positive identification from any prober,
|
|
# it asks for the name of the charset identified. If the prober queried is a
|
|
# Hebrew model prober, the model prober forwards the call to the
|
|
# HebrewProber to make the final decision. In the HebrewProber, the
|
|
# decision is made according to the final-letters scores maintained and Both
|
|
# model probers scores. The answer is returned in the form of the name of the
|
|
# charset identified, either "windows-1255" or "ISO-8859-8".
|
|
|
|
# windows-1255 / ISO-8859-8 code points of interest
|
|
FINAL_KAF = '\xea'
|
|
NORMAL_KAF = '\xeb'
|
|
FINAL_MEM = '\xed'
|
|
NORMAL_MEM = '\xee'
|
|
FINAL_NUN = '\xef'
|
|
NORMAL_NUN = '\xf0'
|
|
FINAL_PE = '\xf3'
|
|
NORMAL_PE = '\xf4'
|
|
FINAL_TSADI = '\xf5'
|
|
NORMAL_TSADI = '\xf6'
|
|
|
|
# Minimum Visual vs Logical final letter score difference.
|
|
# If the difference is below this, don't rely solely on the final letter score distance.
|
|
MIN_FINAL_CHAR_DISTANCE = 5
|
|
|
|
# Minimum Visual vs Logical model score difference.
|
|
# If the difference is below this, don't rely at all on the model score distance.
|
|
MIN_MODEL_DISTANCE = 0.01
|
|
|
|
VISUAL_HEBREW_NAME = "ISO-8859-8"
|
|
LOGICAL_HEBREW_NAME = "windows-1255"
|
|
|
|
class HebrewProber(CharSetProber):
|
|
def __init__(self):
|
|
CharSetProber.__init__(self)
|
|
self._mLogicalProber = None
|
|
self._mVisualProber = None
|
|
self.reset()
|
|
|
|
def reset(self):
|
|
self._mFinalCharLogicalScore = 0
|
|
self._mFinalCharVisualScore = 0
|
|
# The two last characters seen in the previous buffer,
|
|
# mPrev and mBeforePrev are initialized to space in order to simulate a word
|
|
# delimiter at the beginning of the data
|
|
self._mPrev = ' '
|
|
self._mBeforePrev = ' '
|
|
# These probers are owned by the group prober.
|
|
|
|
def set_model_probers(self, logicalProber, visualProber):
|
|
self._mLogicalProber = logicalProber
|
|
self._mVisualProber = visualProber
|
|
|
|
def is_final(self, c):
|
|
return c in [FINAL_KAF, FINAL_MEM, FINAL_NUN, FINAL_PE, FINAL_TSADI]
|
|
|
|
def is_non_final(self, c):
|
|
# The normal Tsadi is not a good Non-Final letter due to words like
|
|
# 'lechotet' (to chat) containing an apostrophe after the tsadi. This
|
|
# apostrophe is converted to a space in FilterWithoutEnglishLetters causing
|
|
# the Non-Final tsadi to appear at an end of a word even though this is not
|
|
# the case in the original text.
|
|
# The letters Pe and Kaf rarely display a related behavior of not being a
|
|
# good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak' for
|
|
# example legally end with a Non-Final Pe or Kaf. However, the benefit of
|
|
# these letters as Non-Final letters outweighs the damage since these words
|
|
# are quite rare.
|
|
return c in [NORMAL_KAF, NORMAL_MEM, NORMAL_NUN, NORMAL_PE]
|
|
|
|
def feed(self, aBuf):
|
|
# Final letter analysis for logical-visual decision.
|
|
# Look for evidence that the received buffer is either logical Hebrew or
|
|
# visual Hebrew.
|
|
# The following cases are checked:
|
|
# 1) A word longer than 1 letter, ending with a final letter. This is an
|
|
# indication that the text is laid out "naturally" since the final letter
|
|
# really appears at the end. +1 for logical score.
|
|
# 2) A word longer than 1 letter, ending with a Non-Final letter. In normal
|
|
# Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi, should not end with
|
|
# the Non-Final form of that letter. Exceptions to this rule are mentioned
|
|
# above in isNonFinal(). This is an indication that the text is laid out
|
|
# backwards. +1 for visual score
|
|
# 3) A word longer than 1 letter, starting with a final letter. Final letters
|
|
# should not appear at the beginning of a word. This is an indication that
|
|
# the text is laid out backwards. +1 for visual score.
|
|
#
|
|
# The visual score and logical score are accumulated throughout the text and
|
|
# are finally checked against each other in GetCharSetName().
|
|
# No checking for final letters in the middle of words is done since that case
|
|
# is not an indication for either Logical or Visual text.
|
|
#
|
|
# We automatically filter out all 7-bit characters (replace them with spaces)
|
|
# so the word boundary detection works properly. [MAP]
|
|
|
|
if self.get_state() == constants.eNotMe:
|
|
# Both model probers say it's not them. No reason to continue.
|
|
return constants.eNotMe
|
|
|
|
aBuf = self.filter_high_bit_only(aBuf)
|
|
|
|
for cur in aBuf:
|
|
if cur == ' ':
|
|
# We stand on a space - a word just ended
|
|
if self._mBeforePrev != ' ':
|
|
# next-to-last char was not a space so self._mPrev is not a 1 letter word
|
|
if self.is_final(self._mPrev):
|
|
# case (1) [-2:not space][-1:final letter][cur:space]
|
|
self._mFinalCharLogicalScore += 1
|
|
elif self.is_non_final(self._mPrev):
|
|
# case (2) [-2:not space][-1:Non-Final letter][cur:space]
|
|
self._mFinalCharVisualScore += 1
|
|
else:
|
|
# Not standing on a space
|
|
if (self._mBeforePrev == ' ') and (self.is_final(self._mPrev)) and (cur != ' '):
|
|
# case (3) [-2:space][-1:final letter][cur:not space]
|
|
self._mFinalCharVisualScore += 1
|
|
self._mBeforePrev = self._mPrev
|
|
self._mPrev = cur
|
|
|
|
# Forever detecting, till the end or until both model probers return eNotMe (handled above)
|
|
return constants.eDetecting
|
|
|
|
def get_charset_name(self):
|
|
# Make the decision: is it Logical or Visual?
|
|
# If the final letter score distance is dominant enough, rely on it.
|
|
finalsub = self._mFinalCharLogicalScore - self._mFinalCharVisualScore
|
|
if finalsub >= MIN_FINAL_CHAR_DISTANCE:
|
|
return LOGICAL_HEBREW_NAME
|
|
if finalsub <= -MIN_FINAL_CHAR_DISTANCE:
|
|
return VISUAL_HEBREW_NAME
|
|
|
|
# It's not dominant enough, try to rely on the model scores instead.
|
|
modelsub = self._mLogicalProber.get_confidence() - self._mVisualProber.get_confidence()
|
|
if modelsub > MIN_MODEL_DISTANCE:
|
|
return LOGICAL_HEBREW_NAME
|
|
if modelsub < -MIN_MODEL_DISTANCE:
|
|
return VISUAL_HEBREW_NAME
|
|
|
|
# Still no good, back to final letter distance, maybe it'll save the day.
|
|
if finalsub < 0.0:
|
|
return VISUAL_HEBREW_NAME
|
|
|
|
# (finalsub > 0 - Logical) or (don't know what to do) default to Logical.
|
|
return LOGICAL_HEBREW_NAME
|
|
|
|
def get_state(self):
|
|
# Remain active as long as any of the model probers are active.
|
|
if (self._mLogicalProber.get_state() == constants.eNotMe) and \
|
|
(self._mVisualProber.get_state() == constants.eNotMe):
|
|
return constants.eNotMe
|
|
return constants.eDetecting
|