Proprietary · Unicode · All Languages

HomoglyphDetector™

Visual Lookalike Character Identification System

HomoglyphDetector™ is a specialized sub-component of WatermarkScanner™ focused exclusively on identifying Unicode homoglyph substitutions — characters from different scripts that are visually identical but different code points. These substitutions are used to embed hidden identifiers, track authorship, or evade text processing tools.

How It Works

1

Script-Aware Parsing

Identifies the expected Unicode script for each word based on the document's primary language. For an English document, all characters should be U+0041–U+007A (Basic Latin). Characters from other scripts that visually resemble Latin are flagged.

2

Homoglyph Table Lookup

Checks flagged characters against a 500+ entry homoglyph lookup table covering: Cyrillic/Latin pairs (а/a, с/c, е/e, о/o, р/p, х/x, у/y), Greek/Latin pairs (α/a, ο/o, κ/k), and other confusable Unicode pairs.

3

Context Validation

Runs context checks to reduce false positives: mixed-script words in multilingual documents are not flagged if the context indicates legitimate language switching (e.g., a Cyrillic word in a Russian passage within an English document).

4

Substitution Reporting

Generates a character-level report listing: original character, Unicode code point, detected homoglyph target, word position, and confidence score. Also provides the cleaned text with all homoglyphs replaced by their standard equivalents.

Key Metrics

500+
Homoglyph pairs
Latin, Cyrillic, Greek, Armenian, others
Scripts covered
99.9%
Detection accuracy
< 0.1%
False positive rate
WatermarkScanner™
Part of
< 2ms per 1000 chars
Processing speed

Use Cases

  • Detecting authorship-tracking homoglyph marks in shared documents
  • NLP pipeline normalisation — ensuring consistent character encoding
  • Security audit of text that may contain hidden script injections
  • Cleaning text before AI processing to prevent encoding attacks

Try HomoglyphDetector™ Now

Powered by our proprietary technology stack. Available directly in the TextHumanize tools and via REST API.

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