Lexical obfuscation involves altering word forms while keeping meaning recoverable for humans. Common techniques include: substituting words with similar-sounding terms or emojis (e.g., using 🍇 for “grape”), character-level modifications (l33tspeak, zero-width characters), and phonetic/visual similarity. These methods exploit simple keyword-based moderation systems that rely on exact matching. While basic obfuscation bypasses dictionary filters, advanced detection using context analysis, semantic models, and pattern recognition can identify these attempts. Effectiveness depends on moderation sophistication—simple systems are easily fooled, while ML-based approaches adapt to new patterns.