glin-profanity

┌─────────────────────────────────────────────────────────────────────────────┐
│                           GLIN PROFANITY v3                                 │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│   Input Text ──►  Unicode       ──►  Leetspeak    ──►  Dictionary  ──► ML  │
│                   Normalization      Detection         Matching        Check│
│                   (homoglyphs)       (f4ck→fuck)       (24 langs)     (opt) │
│                                                                             │
│   "fսck"     ──►  "fuck"        ──►  "fuck"       ──►  MATCH       ──► ✓   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

npm install glin-profanity

pip install glin-profanity

import { checkProfanity, Filter } from 'glin-profanity';

// Simple check
const result = checkProfanity("This is f4ck1ng bad", {
  detectLeetspeak: true,
  languages: ['english']
});

result.containsProfanity  // true
result.profaneWords       // ['fucking']

// With replacement
const filter = new Filter({
  replaceWith: '***',
  detectLeetspeak: true
});
filter.checkProfanity("sh1t happens").processedText  // "*** happens"

from glin_profanity import Filter

filter = Filter({"languages": ["english"], "replace_with": "***"})

filter.is_profane("damn this")           # True
filter.check_profanity("damn this")      # Full result object

import { useProfanityChecker } from 'glin-profanity';

function ChatInput() {
  const { result, checkText } = useProfanityChecker({
    detectLeetspeak: true
  });

  return (
     checkText(e.target.value)} />
    {result?.containsProfanity && Clean up your language}
  );
}

flowchart LR
    subgraph Input
        A[Raw Text]
    end

    subgraph Processing
        B[Unicode Normalizer]
        C[Leetspeak Decoder]
        D[Word Tokenizer]
    end

    subgraph Detection
        E[Dictionary Matcher]
        F[Fuzzy Matcher]
        G[ML Toxicity Model]
    end

    subgraph Output
        H[Result Object]
    end

    A --> B --> C --> D
    D --> E --> H
    D --> F --> H
    D -.->|Optional| G -.-> H

const filter = new Filter({
  detectLeetspeak: true,
  leetspeakLevel: 'aggressive'  // basic | moderate | aggressive
});

filter.isProfane('f4ck');     // true
filter.isProfane('5h1t');     // true
filter.isProfane('@$$');      // true
filter.isProfane('ph.u" "ck'); // true (aggressive mode)

const filter = new Filter({ normalizeUnicode: true });

filter.isProfane('fսck');   // true (Armenian 'ս' → 'u')
filter.isProfane('shіt');   // true (Cyrillic 'і' → 'i')
filter.isProfane('ƒuck');   // true (Latin 'ƒ' → 'f')

import { loadToxicityModel, checkToxicity } from 'glin-profanity/ml';

await loadToxicityModel({ threshold: 0.9 });

const result = await checkToxicity("You're the worst player ever");
// { toxic: true, categories: { toxicity: 0.92, insult: 0.87, ... } }

# Clone the repo
git clone https://github.com/GLINCKER/glin-profanity.git
cd glin-profanity/packages/js

# Install dependencies
npm install

# Start the local testing server
npm run dev:playground

{
  "mcpServers": {
    "glin-profanity": {
      "command": "npx",
      "args": ["-y", "glin-profanity-mcp"]
    }
  }
}

{
  "mcpServers": {
    "glin-profanity": {
      "command": "npx",
      "args": ["-y", "glin-profanity-mcp"]
    }
  }
}

"Check this user comment for profanity using glin-profanity"
"Validate this blog post content with high strictness"
"Batch check these 50 messages for any inappropriate content"
"Analyze this medical text with the medical domain context"

import { PromptInjectionScanner, SecretsScanner, PiiScanner, Vault, scanAll } from 'glin-profanity/scanners';