Triksha - LLM Security Testing Platform

📋 Product Overview

Triksha is a comprehensive security testing platform designed specifically for Large Language Models (LLMs). It provides organizations with the tools needed to identify, analyze, and mitigate potential security vulnerabilities in their AI models.

Core Value Proposition

• Proactive Security: Identify vulnerabilities before they can be exploited
• Comprehensive Testing: Multi-layered approach to security assessment
• Actionable Insights: Clear reporting and remediation recommendations
• Continuous Monitoring: Automated scanning and alerts

🎯 Key Features & Capabilities

1. Security Scanning Modules

Manual Scanning

• Single-prompt vulnerability testing
• Real-time response analysis
• Immediate vulnerability detection
• Custom test case creation

Batch Scanning

• Process multiple prompts simultaneously
• CSV file support for bulk testing
• Configurable QPS (Queries Per Second)
• Progress tracking and reporting

Contextual Analysis

• Deep behavioral analysis
• Model fingerprinting
• Response pattern analysis
• Context-aware vulnerability detection

2. Test Suite Management

Custom Test Cases

• Create and manage test scenarios
• Define expected behaviors
• Set validation rules
• Categorize tests by vulnerability type

Pre-built Templates

• Common vulnerability patterns
• Industry-standard security tests
• Customizable test parameters
• Version control for test cases

3. Monitoring & Automation

Scheduled Scans

• Automated security monitoring
• Configurable scan frequencies
• Custom scan parameters
• Email notifications for critical findings

Real-time Alerts

• Immediate vulnerability notifications
• Severity-based alerting
• Custom alert thresholds
• Integration with notification systems

4. Analysis & Reporting

Vulnerability Assessment

• Detailed scan results
• Severity classification
• Impact analysis
• Remediation recommendations

Performance Metrics

• Response time analysis
• Model behavior patterns
• Success/failure rates
• Historical trend analysis

5. Model Management

Multi-Provider Support

• OpenAI integration
• Anthropic models
• Google AI (Gemini)
• Custom model endpoints

Fine-tuning Capabilities

• Security-focused model training
• Custom dataset creation
• Performance optimization
• Model behavior modification

🔒 Security Categories

1. Prompt Injection

   • Command injection detection
   • System prompt leakage
   • Prompt boundary testing
   • Context manipulation checks

2. Data Leakage

   • Training data extraction
   • Model information disclosure
   • Sensitive data handling
   • Privacy boundary testing

3. Model Behavior

   • Response consistency
   • Output validation
   • Error handling
   • Edge case testing

4. Safety Bounds

   • Content filtering
   • Output sanitization
   • Ethical boundary testing
   • Safety layer validation

5. System Prompt

   • Role adherence
   • Instruction following
   • Context maintenance
   • Behavioral consistency

6. Performance

   • Response time
   • Token optimization
   • Resource utilization
   • Scaling capabilities

💻 Technical Architecture

Frontend Stack

• React + TypeScript
• Tailwind CSS for styling
• shadcn/ui component library
• Vite for build tooling

Backend Infrastructure

• Supabase for data persistence
• Edge Functions for custom logic
• Real-time WebSocket support
• Secure API integrations

Database Schema

• User management
• Test case storage
• Scan results
• Historical data

Security Features

• Row Level Security (RLS)
• API key management
• User authentication
• Data encryption

🚀 Getting Started

Prerequisites

1. Create a Supabase Project:

   • Go to Supabase and create a new project
   • Navigate to Project Settings -> API
   • Copy your Project URL and anon/public key

2. Configure API Keys:

   • OpenAI API key (Get it from OpenAI Platform)
   • Other provider keys as needed

Installation Options

🐳 Using Docker (Recommended)

# Build the Docker image
docker build -t triksha-app .

# Run the container with your environment variables
docker run -p 5173:5173 \
  -e VITE_SUPABASE_URL=your_supabase_url \
  -e VITE_SUPABASE_ANON_KEY=your_supabase_anon_key \
  triksha-app

💻 Local Development

# Clone the repository
git clone <YOUR_GIT_URL>

# Navigate to project directory
cd <YOUR_PROJECT_NAME>

# Install dependencies
npm install

# Create .env file with your Supabase credentials
echo "VITE_SUPABASE_URL=your_supabase_url
VITE_SUPABASE_ANON_KEY=your_supabase_anon_key" > .env

# Start development server
npm run dev

📈 Future Roadmap

Phase 1: Enhanced Analysis

• Advanced fingerprinting algorithms
• Improved vulnerability detection
• Extended model support
• Custom test suite marketplace

Phase 2: Enterprise Features

• Team collaboration tools
• Role-based access control
• Audit logging
• Compliance reporting

Phase 3: Advanced Automation

• CI/CD integration
• Automated remediation
• Advanced analytics
• Custom workflow builder

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details on how to:

• Submit bug reports
• Request features
• Submit pull requests
• Join our community

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

📞 Support

• Documentation: docs.triksha.ai
• Discord Community: Join
• Email Support: [email protected]

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Made with ❤️ by the Triksha Team