Hasher 🔐

A modern, high-performance hash search and generation tool powered by Elasticsearch and Next.js. Search for hash values to find their plaintext origins or generate hashes from any text input.

✨ Features

• 🔍 Hash Lookup: Search for MD5, SHA1, SHA256, SHA512, and Bcrypt hashes
• 🔑 Hash Generation: Generate multiple hash types from plaintext
• 💾 Auto-Indexing: Automatically stores searched plaintext and hashes
• 📊 Elasticsearch Backend: Scalable storage with 10 shards for performance
• 🚀 Bulk Indexing: Import wordlists via command-line script
• 🎨 Modern UI: Beautiful, responsive interface with real-time feedback
• 📋 Copy to Clipboard: One-click copying of any hash value

🏗️ Architecture

┌─────────────┐
│   Next.js   │ ← Modern React UI
│   Frontend  │
└──────┬──────┘
       │
       ↓
┌─────────────┐
│   API       │ ← REST endpoints
│   Routes    │
└──────┬──────┘
       │
       ↓
┌─────────────┐
│Elasticsearch│ ← Distributed storage
│ 10 Shards   │   (localhost:9200)
└─────────────┘

🚀 Quick Start

Prerequisites

• Node.js 18.x or higher
• Elasticsearch 8.x running on localhost:9200
• npm or yarn

Installation

1. Clone the repository

   git clone <repository-url>
   cd hasher
   

2. Install dependencies

   npm install
   

3. Configure Elasticsearch (optional)

   By default, the app connects to http://localhost:9200. To change this:

   export ELASTICSEARCH_NODE=http://your-elasticsearch-host:9200
   

4. Run the development server

   npm run dev
   

5. Open your browser

   Navigate to http://localhost:3000

📖 Usage

Web Interface

1. Search for a Hash

   • Enter any MD5, SHA1, SHA256, or SHA512 hash
   • Click search or press Enter
   • View the plaintext result if found in the database

2. Generate Hashes

   • Enter any plaintext string
   • Get instant hash values for all supported algorithms
   • Hashes are automatically saved for future lookups

Bulk Indexing Script

Index large wordlists or dictionaries:

# Basic usage
npm run index-file wordlist.txt

# With custom batch size
npm run index-file wordlist.txt -- --batch-size 500

# Show help
npm run index-file -- --help

Input file format: One word/phrase per line

password
admin
123456
qwerty

Script features:

• ✅ Bulk indexing with configurable batch size
• ✅ Progress indicator with percentage
• ✅ Error handling and reporting
• ✅ Performance metrics (docs/sec)
• ✅ Automatic index refresh

🔌 API Reference

Search Endpoint

POST /api/search

Search for a hash or generate hashes from plaintext.

Request Body:

{
  "query": "5f4dcc3b5aa765d61d8327deb882cf99"
}

Response (Hash Found):

{
  "found": true,
  "hashType": "md5",
  "hash": "5f4dcc3b5aa765d61d8327deb882cf99",
  "results": [{
    "plaintext": "password",
    "hashes": {
      "md5": "5f4dcc3b5aa765d61d8327deb882cf99",
      "sha1": "5baa61e4c9b93f3f0682250b6cf8331b7ee68fd8",
      "sha256": "5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8",
      "sha512": "b109f3bbbc244eb82441917ed06d618b9008dd09b3befd1b5e07394c706a8bb980b1d7785e5976ec049b46df5f1326af5a2ea6d103fd07c95385ffab0cacbc86"
    }
  }]
}

Response (Plaintext Input):

{
  "found": true,
  "isPlaintext": true,
  "plaintext": "password",
  "hashes": {
    "md5": "5f4dcc3b5aa765d61d8327deb882cf99",
    "sha1": "5baa61e4c9b93f3f0682250b6cf8331b7ee68fd8",
    "sha256": "5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8",
    "sha512": "b109f3bbbc244eb82441917ed06d618b9008dd09b3befd1b5e07394c706a8bb980b1d7785e5976ec049b46df5f1326af5a2ea6d103fd07c95385ffab0cacbc86"
  }
}

Health Check Endpoint

GET /api/health

Check Elasticsearch connection and index status.

Response:

{
  "status": "ok",
  "elasticsearch": {
    "cluster": "elasticsearch",
    "status": "green"
  },
  "index": {
    "exists": true,
    "name": "hasher",
    "stats": {
      "documentCount": 1542,
      "indexSize": 524288
    }
  }
}

🗄️ Elasticsearch Index

Index Configuration

• Name: hasher
• Shards: 10 (for horizontal scaling)
• Replicas: 1 (for redundancy)

Mapping Schema

{
  "plaintext": {
    "type": "text",
    "analyzer": "lowercase_analyzer",
    "fields": {
      "keyword": { "type": "keyword" }
    }
  },
  "md5": { "type": "keyword" },
  "sha1": { "type": "keyword" },
  "sha256": { "type": "keyword" },
  "sha512": { "type": "keyword" },
  "created_at": { "type": "date" }
}

📁 Project Structure

hasher/
├── app/
│   ├── api/
│   │   ├── search/
│   │   │   └── route.ts        # Search endpoint
│   │   └── health/
│   │       └── route.ts        # Health check endpoint
│   ├── layout.tsx              # Root layout
│   ├── page.tsx                # Main UI component
│   └── globals.css             # Global styles
├── lib/
│   ├── elasticsearch.ts        # ES client & index config
│   └── hash.ts                 # Hash utilities
├── scripts/
│   └── index-file.ts           # Bulk indexing script
├── package.json
├── tsconfig.json
├── next.config.ts
└── README.md

🛠️ Development

Build for Production

npm run build
npm run start

Environment Variables

Create a .env.local file:

ELASTICSEARCH_NODE=http://localhost:9200

Linting

npm run lint

🔒 Supported Hash Algorithms

Algorithm	Length (hex)	Detection Pattern
MD5	32	^[a-f0-9]{32}$
SHA1	40	^[a-f0-9]{40}$
SHA256	64	^[a-f0-9]{64}$
SHA512	128	^[a-f0-9]{128}$
Bcrypt	60	^\$2[abxy]\$

🚀 Performance

• Bulk Indexing: ~1000-5000 docs/sec (depending on hardware)
• Search Latency: <50ms (typical)
• Horizontal Scaling: 10 shards for parallel processing
• Auto-refresh: Instant search availability for new documents

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is open source and available under the MIT License.

🙏 Acknowledgments

• Built with Next.js
• Powered by Elasticsearch
• Icons by Lucide
• Styled with Tailwind CSS

📧 Support

For issues, questions, or contributions, please open an issue on GitHub.

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