Ultra-fast content moderation with SymSpell fuzzy matching. Multi-language profanity detection with 100x performance improvement. Simple, modern TypeScript library with severity levels and customizable filtering.

npm version TypeScript License: MIT

• 🚀 100x faster fuzzy matching - SymSpell algorithm (50,000 words/sec vs 500 words/sec)
• 🌍 19 language support - English, Spanish, French, German, Japanese, Korean, Chinese, and more
• 🔍 Smart fuzzy matching - Detects obfuscated words (sh!t, fvck, etc.) with edit distance
• 📊 Severity levels - Configurable filtering based on content severity (LOW to SEVERE)
• 🏷️ Categorization - Hate speech, violence, sexual content, and more
• ⚡ Blazing fast - 571K lookups/second, optimized for real-time moderation
• 🛠️ Customizable - Add custom words, whitelist terms, configure filtering
• 📦 Tree-shakeable - ESM and CJS support with optimal bundle sizes
• 🔒 Type-safe - Full TypeScript support with comprehensive type definitions
• 💾 Memory efficient - ~8MB RAM per language for 5K words

I built ContentShield because existing profanity filters were either:

• ❌ Too slow - Traditional edit distance algorithms are 100x slower
• ❌ English-only - Poor or no multi-language support
• ❌ Over-engineered - Complex APIs for simple tasks
• ❌ Poorly maintained - Abandoned packages with outdated dictionaries

ContentShield is:

• ✅ Blazing fast - SymSpell algorithm gives 100x performance boost
• ✅ Comprehensive - 3,600+ profanity entries across 19 languages
• ✅ Multi-language - Actually works across different languages and scripts
• ✅ Simple - Easy to use with sensible defaults
• ✅ Maintained - Actively developed and improved

Built by Zach Handley for developers who need reliable, fast content moderation without the hassle.

Note on Multi-language Accuracy: While I've done my best to compile accurate profanity databases for all 19 languages using native speaker resources, linguistic databases, and community contributions, some entries may be incorrect or incomplete for languages I don't speak natively. Contributions and corrections are always welcome!

npm install content-shield

yarn add content-shield

pnpm add content-shield

import { detect, filter, isClean, configure } from 'content-shield'
import { EN } from 'content-shield/languages/en'
// Configure once with language data
await configure({ languageData: { en: EN } })
// Quick naughty word check
const isProfane = !(await isClean('Your text here'))
// Get detailed analysis
const result = await detect('Your text here')
console.log(result.hasProfanity, result.matches)
// Filter naughty content
const cleanText = await filter('Your text here')

import {
 ContentShieldDetector,
 SeverityLevel,
 ProfanityCategory,
 FilterMode
} from 'content-shield'
import { EN, ES, FR } from 'content-shield/languages'
// Create a custom multi-language detector
const detector = new ContentShieldDetector({
 languages: ['en', 'es', 'fr'],
 languageData: { en: EN, es: ES, fr: FR },
 minSeverity: SeverityLevel.MODERATE,
 categories: [
 ProfanityCategory.HATE_SPEECH,
 ProfanityCategory.VIOLENCE
 ],
 fuzzyMatching: true,
 fuzzyThreshold: 0.8
})
// Analyze text
const analysis = await detector.analyze('Text to analyze')
// Filter with different modes
const censored = await detector.filter(text, FilterMode.CENSOR) // "f***"
const removed = await detector.filter(text, FilterMode.REMOVE) // ""
const replaced = await detector.filter(text, FilterMode.REPLACE) // "[filtered]"

ContentShield is optimized for tree-shaking - only the languages you import are included in your bundle!

• English only: ~407KB (code + EN data)
• 3 languages: ~671KB (code + 3 languages)
• All 17 languages: ~2.3MB (code + all data)

This means your users only download what they need. Import Spanish? Only Spanish data is bundled. Perfect for keeping those bundle sizes clean (unlike the words we're detecting)! 📦✨

import { detect, filter, FilterMode, configure } from 'content-shield'
import { EN } from 'content-shield/languages/en'
// Configure once at app startup
await configure({ languageData: { en: EN } })
async function moderateMessage(message: string) {
 const result = await detect(message)
 if (result.hasProfanity) {
 // Uh oh, someone's been naughty!
 console.log(`Naughty words detected: ${result.totalMatches} matches`)
 // Return filtered message
 return await filter(message, FilterMode.CENSOR)
 }
 return message
}

import { isClean, configure } from 'content-shield'
import { EN } from 'content-shield/languages/en'
// Configure once at app startup
await configure({ languageData: { en: EN } })
async function validateUsername(username: string) {
 const clean = await isClean(username)
 if (!clean) {
 throw new Error('Username contains naughty content')
 }
 return username
}

import { ContentShieldDetector, SeverityLevel } from 'content-shield'
import { EN, ES } from 'content-shield/languages'
const detector = new ContentShieldDetector({
 minSeverity: SeverityLevel.HIGH, // Only catch the naughtiest words
 languages: ['en', 'es'],
 languageData: { en: EN, es: ES }
})
async function filterUserContent(content: string) {
 const result = await detector.analyze(content)
 if (result.maxSeverity >= SeverityLevel.SEVERE) {
 // Block content entirely
 return null
 } else if (result.hasProfanity) {
 // Filter but allow
 return await detector.filter(content)
 }
 return content
}

• detect(text: string): Promise<DetectionResult> - Analyze text for naughty words
• filter(text: string, mode?: FilterMode): Promise<string> - Filter naughty words from text
• isClean(text: string): Promise<boolean> - Check if text is squeaky clean

const detector = new ContentShieldDetector(config)
await detector.analyze(text, options) // Full analysis
await detector.isProfane(text) // Boolean check
await detector.filter(text, mode) // Filter text
detector.updateConfig(newConfig) // Update configuration
detector.getConfig() // Get current config

interface DetectorConfig {
 languages: LanguageCode[] // Languages to detect
 minSeverity: SeverityLevel // Minimum severity to flag
 categories: ProfanityCategory[] // Categories to detect
 fuzzyMatching: boolean // Enable fuzzy matching
 fuzzyThreshold: number // Fuzzy matching threshold (0-1)
 customWords: CustomWord[] // Additional words to detect
 whitelist: string[] // Words to never flag
 detectAlternateScripts: boolean // Detect in other alphabets
 normalizeText: boolean // Normalize before detection
 replacementChar: string // Character for censoring
 preserveStructure: boolean // Keep word structure when censoring
}

enum SeverityLevel {
 LOW = 1, // Mildly naughty
 MODERATE = 2, // Pretty naughty
 HIGH = 3, // Very naughty
 SEVERE = 4 // Extremely naughty (the naughtiest!)
}

enum ProfanityCategory {
 GENERAL = 'general',
 SEXUAL = 'sexual',
 VIOLENCE = 'violence',
 HATE_SPEECH = 'hate_speech',
 DISCRIMINATION = 'discrimination',
 SUBSTANCE_ABUSE = 'substance_abuse',
 RELIGIOUS = 'religious',
 POLITICAL = 'political'
}

ContentShield speaks 17 languages fluently (and knows all the naughty words in each):

• 🇺🇸 English (en) - 714 entries
• 🇯🇵 Japanese (ja) - 247 entries
• 🇰🇷 Korean (ko) - 240 entries
• 🇨🇳 Chinese (zh) - 230 entries
• 🇳🇱 Dutch (nl) - 230 entries
• 🇫🇷 French (fr) - 229 entries
• 🇮🇹 Italian (it) - 229 entries
• 🇩🇪 German (de) - 226 entries
• 🇪🇸 Spanish (es) - 221 entries
• 🇵🇹 Portuguese (pt) - 218 entries
• 🇷🇺 Russian (ru) - 215 entries
• 🇵🇱 Polish (pl) - 204 entries
• 🇹🇷 Turkish (tr) - 203 entries
• 🇮🇱 Hebrew (he) - 200 entries
• 🇸🇪 Swedish (sv) - 179 entries
• 🇸🇦 Arabic (ar) - 105 entries
• 🇮🇳 Hindi (hi) - 101 entries

Total: 3,600+ naughty words across all languages 🚫

Use 'auto' for automatic language detection, or specify exact languages for better performance.

import { ContentShieldDetector, SeverityLevel, ProfanityCategory } from 'content-shield'
import { EN } from 'content-shield/languages/en'
const detector = new ContentShieldDetector({
 languages: ['en'],
 languageData: { en: EN },
 customWords: [
 {
 word: 'frack', // Custom sci-fi profanity
 language: 'en',
 severity: SeverityLevel.MODERATE,
 categories: [ProfanityCategory.GENERAL],
 variations: ['fr@ck', 'fr4ck'],
 caseSensitive: false
 }
 ],
 whitelist: ['hello', 'world'] // Never flag these words
})

Choose how to handle those naughty words:

enum FilterMode {
 CENSOR = 'censor', // Replace with * (f***)
 REMOVE = 'remove', // Remove entirely (poof!)
 REPLACE = 'replace', // Replace with [filtered]
 DETECT_ONLY = 'detect_only' // Just detect, don't modify
}

import {
 createEnglishDetector,
 createSpanishDetector,
 createMultiLanguageDetector
} from 'content-shield'
import { EN, ES, FR } from 'content-shield/languages'
const englishOnly = createEnglishDetector({ languageData: { en: EN } })
const spanishOnly = createSpanishDetector({ languageData: { es: ES } })
const multiLang = createMultiLanguageDetector(
 ['en', 'es', 'fr'],
 { languageData: { en: EN, es: ES, fr: FR } }
)

ContentShield delivers exceptional performance:

• Detection Speed: ~14,000 words/second
• Large Text Matching: ~15ms for 10,000 words
• Batch Processing: 555,556 words/second throughput
• Memory Efficiency: ~226 bytes per word in trie structure
• Fuzzy Matching: Configurable threshold for speed vs accuracy
• Language Detection: Fast language identification
• Tree-shaking: Import only what you need
• Caching: Intelligent caching with sub-millisecond cached lookups

# Install dependencies
npm install
# Build the library
npm run build
# Run tests
npm test
# Run with coverage
npm run test:coverage
# Lint code
npm run lint
# Format code
npm run format

Contributions are welcome! This project benefits from community input. Here's how you can help:

• Add new languages - Help expand multi-language support
• Improve detection accuracy - Suggest new words or fix false positives
• Performance optimizations - Make the library even faster
• Documentation - Improve examples, guides, and API docs
• Bug reports - Found an issue? Let us know!
• Feature requests - Have an idea? Open a discussion!

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Run the test suite (pnpm test)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Submit a pull request

Adding a new language? Great! Here's what we need:

• Profanity entries in /data/languages/{code}/profanity.json
• Severity classifications
• Category mappings
• Common variations and obfuscations
• Test cases to verify detection

See existing language files for format examples.

MIT © Zach Handley

• 📚 Documentation
• 🐛 Bug Reports
• 💬 Discussions

The profanity databases in this library were compiled from various open-source resources, linguistic databases, and community contributions. Here are the primary sources for each language:

• LDNOOBW
• zautumnz/profane-words
• coffee-and-fun/google-profanity-words
• Carnegie Mellon University offensive word list (1,300+ terms)
• Wiktionary English swear words directory
• NoSwearing.com dictionary
• Regional slang databases (UK, US, Australian)

• LDNOOBW
• Wikipedia Spanish Profanity article
• Regional Spanish language databases

• LDNOOBW
• darwiin/french-badwords-list
• Wiktionary French insults and vulgar terms categories
• Quebec French profanity resources
• Linguistic research on French slang and verlan

• LDNOOBW
• getoliverleon/badwords-adult-DE
• Wiktionary German insult directory

• LDNOOBW
• krusk8/italian-badwords-list
• napolux/paroleitaliane
• Wikipedia Italian Profanity article
• Regional dialect research (Venetian, Tuscan, Neapolitan, Sicilian)

• LDNOOBW
• Wikipedia Portuguese Profanity article
• Brazilian and European Portuguese language resources

• censor-text/profanity-list
• LDNOOBW
• denexapp/russian-bad-words
• nickname76/russian-swears
• Wikipedia Mat (profanity) article
• Russian internet culture and gaming communities

• censor-text/profanity-list
• LDNOOBW
• LTL School Chinese Swear Words Guide
• Wikipedia: Mandarin Chinese profanity, Cantonese profanity
• Internet meme culture (Grass Mud Horse, River Crab)

• LDNOOBW
• censor-text/profanity-list
• Wikipedia Japanese profanity article
• Japanese language learning resources (Lingopie, Migaku, Cotoacademy)
• Japanese internet culture (2ch/5ch slang databases)

• LDNOOBW
• doublems/korean-bad-words
• yoonheyjung/badwords-ko
• Tanat05/korean-profanity-resources
• Wikipedia Korean profanity article
• Online Korean language learning resources (FluentU, Ling, Tandem)

• uxbert/arabic_bad_dirty_word_filter_list
• censor-text/profanity-list
• shammur/Arabic-Offensive-Multi-Platform-SocialMedia-Comment-Dataset
• Arabic-for-Nerds: Comprehensive curse word documentation
• Multiple dialect-specific linguistic studies

• LDNOOBW
• Karl Rock's Hindi Swear Words Blog
• Kaggle Hindi Swear Words Dataset (150+ words)
• Wikipedia: Hindustani Profanity

• Wikipedia Dutch Profanity article
• Wiktionary Dutch insult directory (445+ entries)
• Dutch language learning resources (dutchreview.com, learndutch.org, lingopie.com)

• LDNOOBW
• Wiktionary: Kategori:Svenska/Svordomar
• Wikipedia: Swedish profanity
• Language learning resources (Lingvist, Lingopie)

• Wikipedia: Polish profanity
• YouSwear.com Polish section
• Toolpaq Polish curse words guide
• Wiktionary Polish vulgarisms index

• Nimrod007 GitHub Gist
• kkrypt0nn/wordlists
• dsojevic/profanity-list
• Kveller.com: "All the Hebrew Curses You Need to Know"
• iGoogledIsrael: Hebrew profanity guide
• Reddit r/hebrew

• Turkish language learning resources
• Turkish social media and internet slang databases
• Linguistic resources and native speaker databases

Special thanks to all the open-source contributors, linguists, and native speakers who have helped compile these databases. If you notice any errors or have suggestions for improvements, please open an issue or submit a pull request!

Note: This library is designed for content moderation and educational purposes. Use it to keep things clean (or at least know when they're not)! Please use responsibly and in accordance with your platform's community guidelines.

Remember: Just because we detect naughty words doesn't mean we can't have fun doing it! 😄