Spam Detection
Spam Detection
Over 200 spam patterns are actively checked against every message. The system uses text normalization to defeat evasion techniques.
Banned Words
Messages containing known spam phrases from a maintained word list
Scam Patterns
"Contact me if you hold X", fake wallet/payment scams, rug pull indicators, phishing attempts
Fake Admins
Users impersonating admins via similar names, titles like "CEO", "Dev", or "Owner", or matching the group/token name
Fake Contracts
Users with blockchain addresses in their display names to trick others
Fake Bots
Impostor bots using homograph/lookalike characters in usernames (e.g., capital "I" instead of "l")
Text Normalization
Cyrillic-to-Latin conversion, Unicode mapping, and number-to-letter substitution (0→O, 1→I) to catch evasion tricks
Image Hash Matching
Perceptual image hashing (DifferenceHash) detects copied or slightly modified spam images, even after cropping or color changes
Similar Name Detection
Levenshtein distance algorithm catches names visually similar to admin names or the group name
Last updated