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554 lines
17 KiB
Python
554 lines
17 KiB
Python
from functools import lru_cache
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from typing import List, Optional
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from .constant import COMMON_SAFE_ASCII_CHARACTERS, UNICODE_SECONDARY_RANGE_KEYWORD
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from .utils import (
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is_accentuated,
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is_ascii,
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is_case_variable,
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is_cjk,
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is_emoticon,
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is_hangul,
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is_hiragana,
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is_katakana,
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is_latin,
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is_punctuation,
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is_separator,
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is_symbol,
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is_thai,
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is_unprintable,
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remove_accent,
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unicode_range,
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)
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class MessDetectorPlugin:
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"""
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Base abstract class used for mess detection plugins.
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All detectors MUST extend and implement given methods.
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"""
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def eligible(self, character: str) -> bool:
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"""
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Determine if given character should be fed in.
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"""
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raise NotImplementedError # pragma: nocover
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def feed(self, character: str) -> None:
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"""
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The main routine to be executed upon character.
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Insert the logic in witch the text would be considered chaotic.
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"""
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raise NotImplementedError # pragma: nocover
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def reset(self) -> None: # pragma: no cover
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"""
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Permit to reset the plugin to the initial state.
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"""
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raise NotImplementedError
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@property
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def ratio(self) -> float:
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"""
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Compute the chaos ratio based on what your feed() has seen.
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Must NOT be lower than 0.; No restriction gt 0.
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"""
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raise NotImplementedError # pragma: nocover
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class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._punctuation_count: int = 0
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self._symbol_count: int = 0
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self._character_count: int = 0
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self._last_printable_char: Optional[str] = None
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self._frenzy_symbol_in_word: bool = False
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def eligible(self, character: str) -> bool:
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return character.isprintable()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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character != self._last_printable_char
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and character not in COMMON_SAFE_ASCII_CHARACTERS
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):
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if is_punctuation(character):
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self._punctuation_count += 1
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elif (
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character.isdigit() is False
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and is_symbol(character)
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and is_emoticon(character) is False
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):
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self._symbol_count += 2
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self._last_printable_char = character
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def reset(self) -> None: # pragma: no cover
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self._punctuation_count = 0
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self._character_count = 0
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self._symbol_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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ratio_of_punctuation: float = (
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self._punctuation_count + self._symbol_count
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) / self._character_count
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return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0
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class TooManyAccentuatedPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._character_count: int = 0
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self._accentuated_count: int = 0
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def eligible(self, character: str) -> bool:
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return character.isalpha()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if is_accentuated(character):
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self._accentuated_count += 1
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def reset(self) -> None: # pragma: no cover
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self._character_count = 0
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self._accentuated_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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ratio_of_accentuation: float = self._accentuated_count / self._character_count
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return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0
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class UnprintablePlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._unprintable_count: int = 0
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self._character_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if is_unprintable(character):
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self._unprintable_count += 1
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self._character_count += 1
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def reset(self) -> None: # pragma: no cover
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self._unprintable_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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return (self._unprintable_count * 8) / self._character_count
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class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._successive_count: int = 0
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self._character_count: int = 0
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self._last_latin_character: Optional[str] = None
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def eligible(self, character: str) -> bool:
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return character.isalpha() and is_latin(character)
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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self._last_latin_character is not None
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and is_accentuated(character)
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and is_accentuated(self._last_latin_character)
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):
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if character.isupper() and self._last_latin_character.isupper():
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self._successive_count += 1
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# Worse if its the same char duplicated with different accent.
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if remove_accent(character) == remove_accent(self._last_latin_character):
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self._successive_count += 1
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self._last_latin_character = character
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def reset(self) -> None: # pragma: no cover
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self._successive_count = 0
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self._character_count = 0
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self._last_latin_character = None
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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return (self._successive_count * 2) / self._character_count
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class SuspiciousRange(MessDetectorPlugin):
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def __init__(self) -> None:
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self._suspicious_successive_range_count: int = 0
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self._character_count: int = 0
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self._last_printable_seen: Optional[str] = None
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def eligible(self, character: str) -> bool:
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return character.isprintable()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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character.isspace()
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or is_punctuation(character)
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or character in COMMON_SAFE_ASCII_CHARACTERS
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):
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self._last_printable_seen = None
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return
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if self._last_printable_seen is None:
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self._last_printable_seen = character
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return
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unicode_range_a: Optional[str] = unicode_range(self._last_printable_seen)
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unicode_range_b: Optional[str] = unicode_range(character)
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if is_suspiciously_successive_range(unicode_range_a, unicode_range_b):
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self._suspicious_successive_range_count += 1
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self._last_printable_seen = character
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def reset(self) -> None: # pragma: no cover
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self._character_count = 0
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self._suspicious_successive_range_count = 0
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self._last_printable_seen = None
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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ratio_of_suspicious_range_usage: float = (
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self._suspicious_successive_range_count * 2
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) / self._character_count
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if ratio_of_suspicious_range_usage < 0.1:
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return 0.0
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return ratio_of_suspicious_range_usage
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class SuperWeirdWordPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._word_count: int = 0
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self._bad_word_count: int = 0
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self._foreign_long_count: int = 0
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self._is_current_word_bad: bool = False
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self._foreign_long_watch: bool = False
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self._character_count: int = 0
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self._bad_character_count: int = 0
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self._buffer: str = ""
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self._buffer_accent_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if character.isalpha():
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self._buffer += character
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if is_accentuated(character):
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self._buffer_accent_count += 1
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if (
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self._foreign_long_watch is False
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and (is_latin(character) is False or is_accentuated(character))
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and is_cjk(character) is False
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and is_hangul(character) is False
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and is_katakana(character) is False
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and is_hiragana(character) is False
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and is_thai(character) is False
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):
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self._foreign_long_watch = True
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return
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if not self._buffer:
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return
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if (
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character.isspace() or is_punctuation(character) or is_separator(character)
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) and self._buffer:
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self._word_count += 1
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buffer_length: int = len(self._buffer)
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self._character_count += buffer_length
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if buffer_length >= 4:
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if self._buffer_accent_count / buffer_length > 0.34:
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self._is_current_word_bad = True
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# Word/Buffer ending with a upper case accentuated letter are so rare,
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# that we will consider them all as suspicious. Same weight as foreign_long suspicious.
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if is_accentuated(self._buffer[-1]) and self._buffer[-1].isupper():
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self._foreign_long_count += 1
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self._is_current_word_bad = True
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if buffer_length >= 24 and self._foreign_long_watch:
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self._foreign_long_count += 1
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self._is_current_word_bad = True
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if self._is_current_word_bad:
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self._bad_word_count += 1
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self._bad_character_count += len(self._buffer)
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self._is_current_word_bad = False
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self._foreign_long_watch = False
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self._buffer = ""
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self._buffer_accent_count = 0
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elif (
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character not in {"<", ">", "-", "=", "~", "|", "_"}
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and character.isdigit() is False
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and is_symbol(character)
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):
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self._is_current_word_bad = True
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self._buffer += character
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def reset(self) -> None: # pragma: no cover
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self._buffer = ""
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self._is_current_word_bad = False
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self._foreign_long_watch = False
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self._bad_word_count = 0
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self._word_count = 0
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self._character_count = 0
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self._bad_character_count = 0
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self._foreign_long_count = 0
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@property
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def ratio(self) -> float:
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if self._word_count <= 10 and self._foreign_long_count == 0:
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return 0.0
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return self._bad_character_count / self._character_count
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class CjkInvalidStopPlugin(MessDetectorPlugin):
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"""
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GB(Chinese) based encoding often render the stop incorrectly when the content does not fit and
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can be easily detected. Searching for the overuse of '丅' and '丄'.
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"""
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def __init__(self) -> None:
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self._wrong_stop_count: int = 0
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self._cjk_character_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if character in {"丅", "丄"}:
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self._wrong_stop_count += 1
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return
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if is_cjk(character):
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self._cjk_character_count += 1
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def reset(self) -> None: # pragma: no cover
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self._wrong_stop_count = 0
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self._cjk_character_count = 0
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@property
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def ratio(self) -> float:
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if self._cjk_character_count < 16:
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return 0.0
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return self._wrong_stop_count / self._cjk_character_count
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class ArchaicUpperLowerPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._buf: bool = False
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self._character_count_since_last_sep: int = 0
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self._successive_upper_lower_count: int = 0
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self._successive_upper_lower_count_final: int = 0
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self._character_count: int = 0
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self._last_alpha_seen: Optional[str] = None
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self._current_ascii_only: bool = True
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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is_concerned = character.isalpha() and is_case_variable(character)
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chunk_sep = is_concerned is False
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if chunk_sep and self._character_count_since_last_sep > 0:
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if (
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self._character_count_since_last_sep <= 64
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and character.isdigit() is False
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and self._current_ascii_only is False
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):
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self._successive_upper_lower_count_final += (
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self._successive_upper_lower_count
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)
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self._successive_upper_lower_count = 0
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self._character_count_since_last_sep = 0
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self._last_alpha_seen = None
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self._buf = False
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self._character_count += 1
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self._current_ascii_only = True
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return
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if self._current_ascii_only is True and is_ascii(character) is False:
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self._current_ascii_only = False
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if self._last_alpha_seen is not None:
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if (character.isupper() and self._last_alpha_seen.islower()) or (
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character.islower() and self._last_alpha_seen.isupper()
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):
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if self._buf is True:
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self._successive_upper_lower_count += 2
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self._buf = False
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else:
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self._buf = True
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else:
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self._buf = False
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self._character_count += 1
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self._character_count_since_last_sep += 1
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self._last_alpha_seen = character
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def reset(self) -> None: # pragma: no cover
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self._character_count = 0
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self._character_count_since_last_sep = 0
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self._successive_upper_lower_count = 0
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self._successive_upper_lower_count_final = 0
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self._last_alpha_seen = None
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self._buf = False
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self._current_ascii_only = True
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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return self._successive_upper_lower_count_final / self._character_count
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@lru_cache(maxsize=1024)
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def is_suspiciously_successive_range(
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unicode_range_a: Optional[str], unicode_range_b: Optional[str]
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) -> bool:
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"""
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Determine if two Unicode range seen next to each other can be considered as suspicious.
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"""
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if unicode_range_a is None or unicode_range_b is None:
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return True
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if unicode_range_a == unicode_range_b:
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return False
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if "Latin" in unicode_range_a and "Latin" in unicode_range_b:
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return False
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if "Emoticons" in unicode_range_a or "Emoticons" in unicode_range_b:
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return False
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# Latin characters can be accompanied with a combining diacritical mark
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# eg. Vietnamese.
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if ("Latin" in unicode_range_a or "Latin" in unicode_range_b) and (
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"Combining" in unicode_range_a or "Combining" in unicode_range_b
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):
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return False
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keywords_range_a, keywords_range_b = unicode_range_a.split(
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" "
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), unicode_range_b.split(" ")
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for el in keywords_range_a:
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if el in UNICODE_SECONDARY_RANGE_KEYWORD:
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continue
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if el in keywords_range_b:
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return False
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# Japanese Exception
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range_a_jp_chars, range_b_jp_chars = (
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unicode_range_a
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in (
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"Hiragana",
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"Katakana",
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),
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unicode_range_b in ("Hiragana", "Katakana"),
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)
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if (range_a_jp_chars or range_b_jp_chars) and (
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"CJK" in unicode_range_a or "CJK" in unicode_range_b
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):
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return False
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if range_a_jp_chars and range_b_jp_chars:
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return False
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if "Hangul" in unicode_range_a or "Hangul" in unicode_range_b:
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if "CJK" in unicode_range_a or "CJK" in unicode_range_b:
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return False
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if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin":
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return False
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# Chinese/Japanese use dedicated range for punctuation and/or separators.
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if ("CJK" in unicode_range_a or "CJK" in unicode_range_b) or (
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unicode_range_a in ["Katakana", "Hiragana"]
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and unicode_range_b in ["Katakana", "Hiragana"]
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):
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if "Punctuation" in unicode_range_a or "Punctuation" in unicode_range_b:
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return False
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if "Forms" in unicode_range_a or "Forms" in unicode_range_b:
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return False
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return True
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@lru_cache(maxsize=2048)
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def mess_ratio(
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decoded_sequence: str, maximum_threshold: float = 0.2, debug: bool = False
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) -> float:
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"""
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Compute a mess ratio given a decoded bytes sequence. The maximum threshold does stop the computation earlier.
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"""
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detectors: List[MessDetectorPlugin] = [
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md_class() for md_class in MessDetectorPlugin.__subclasses__()
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]
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length: int = len(decoded_sequence) + 1
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mean_mess_ratio: float = 0.0
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if length < 512:
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intermediary_mean_mess_ratio_calc: int = 32
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elif length <= 1024:
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intermediary_mean_mess_ratio_calc = 64
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else:
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intermediary_mean_mess_ratio_calc = 128
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for character, index in zip(decoded_sequence + "\n", range(length)):
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for detector in detectors:
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if detector.eligible(character):
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detector.feed(character)
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if (
|
|
index > 0 and index % intermediary_mean_mess_ratio_calc == 0
|
|
) or index == length - 1:
|
|
mean_mess_ratio = sum(dt.ratio for dt in detectors)
|
|
|
|
if mean_mess_ratio >= maximum_threshold:
|
|
break
|
|
|
|
if debug:
|
|
for dt in detectors: # pragma: nocover
|
|
print(dt.__class__, dt.ratio)
|
|
|
|
return round(mean_mess_ratio, 3)
|