TelegramGuard / modules /prefilter.py
ilang-ai
v4.3: pre-filter layer — zero API cost spam defense
27803aa
"""
Pre-filter: catches obvious spam BEFORE burning an AI API call.
Zero cost. Runs on every message. AI only sees what passes all filters.
"""
import re
import time
import logging
logger = logging.getLogger(__name__)
# Spam keyword patterns (multilingual)
SPAM_KEYWORDS = re.compile(
r'加[我微v]|私聊领|免费领|日[赚入]|月入[过百千万]|'
r'代[开做理]|招[代聘]|兼\s*职|刷\s*单|'
r'翻[几十百]倍|稳赚|保本|零风险|'
r'[\U0001F4B0\U0001F4B8\U0001F911]{2,}|' # money emoji spam
r'click here|earn money|work from home|make \$|'
r'free crypto|airdrop|whitelist spot|'
r'join (?:my|our|this) (?:channel|group)|'
r't\.me/(?:joinchat|[+])',
re.IGNORECASE
)
# URL patterns
URL_PATTERN = re.compile(
r'https?://|t\.me/|bit\.ly|tinyurl|wa\.me|'
r'@\w+bot\b',
re.IGNORECASE
)
# Contact info patterns
CONTACT_PATTERN = re.compile(
r'[\U0001F4DE\U0001F4F1]|' # phone emojis
r'(?:whatsapp|telegram|wechat|微信|qq)\s*[::]?\s*\d|'
r'(?:加|add)\s*(?:我|me)',
re.IGNORECASE
)
class APIRateLimiter:
"""Token bucket rate limiter for AI API calls."""
def __init__(self, max_calls=50, window=60):
self.max_calls = max_calls # max calls per window
self.window = window # window in seconds
self.calls = [] # timestamps of recent calls
def can_call(self):
"""Check if we can make another API call."""
now = time.time()
self.calls = [t for t in self.calls if now - t < self.window]
return len(self.calls) < self.max_calls
def record_call(self):
"""Record an API call."""
self.calls.append(time.time())
def remaining(self):
"""How many calls left in current window."""
now = time.time()
self.calls = [t for t in self.calls if now - t < self.window]
return max(0, self.max_calls - len(self.calls))
def is_critical(self):
"""Below 20% budget — switch to sampling mode."""
return self.remaining() < self.max_calls * 0.2
# Global rate limiter: 50 AI calls per minute (adjustable)
api_limiter = APIRateLimiter(max_calls=50, window=60)
def keyword_spam(text):
"""Fast keyword check. Returns True if obvious spam."""
if not text:
return False
# Keyword match + has URL or contact = almost certainly spam
has_keywords = bool(SPAM_KEYWORDS.search(text))
has_url = bool(URL_PATTERN.search(text))
has_contact = bool(CONTACT_PATTERN.search(text))
if has_keywords and (has_url or has_contact):
return True
# Pure contact harvesting: just a contact method, no real conversation
if has_contact and len(text) < 100 and not any(c in text for c in '??'):
return True
return False
def forward_spam(msg):
"""Forwarded message with link/contact = spam."""
if not msg.forward_date:
return False
text = msg.text or msg.caption or ""
if URL_PATTERN.search(text) or CONTACT_PATTERN.search(text):
return True
# Forwarded media with no caption from non-group member = suspicious
if not text and (msg.photo or msg.video or msg.document):
return True
return False
def new_account_spam(user, text):
"""New/suspicious accounts with links = spam."""
if not text or not URL_PATTERN.search(text):
return False
# No username + no profile photo + has link = high spam probability
suspicious = 0
if not user.username:
suspicious += 1
if not user.first_name or len(user.first_name) < 2:
suspicious += 1
# Name is just emojis or special chars
if user.first_name and not any(c.isalpha() for c in user.first_name):
suspicious += 1
return suspicious >= 2
def should_use_ai(msg):
"""Decide if this message needs AI analysis or if we should skip/sample."""
if not api_limiter.can_call():
logger.warning("API rate limit hit — falling back to rules only")
return False
if api_limiter.is_critical():
# Sampling mode: only check 1 in 3 messages
import random
if random.random() > 0.33:
logger.info("API budget critical — sampling mode, skipping this message")
return False
return True
def prefilter(msg, user, text):
"""
Run all pre-filters. Returns:
"spam" — definitely spam, skip AI, nuke immediately
"clean" — definitely clean, skip AI
"ai" — unclear, needs AI analysis
"""
# Layer 1: Forward spam (zero false positive)
if forward_spam(msg):
logger.info("PREFILTER forward_spam: user=" + str(user.id))
return "spam"
# Layer 2: Keyword + link/contact (very high accuracy)
if text and keyword_spam(text):
logger.info("PREFILTER keyword_spam: user=" + str(user.id) + " text=" + text[:50])
return "spam"
# Layer 3: Suspicious new account + link
if new_account_spam(user, text):
logger.info("PREFILTER new_account_spam: user=" + str(user.id))
return "spam"
# Layer 4: No text, no media = nothing to check
if not text and not msg.photo and not msg.video:
return "clean"
# Layer 5: Rate limiter — can we afford an AI call?
if not should_use_ai(msg):
return "clean" # let it through rather than false-positive
# Needs AI
api_limiter.record_call()
return "ai"