Currently, only the latest version of JEPA Real-Time Sentiment Analysis is supported with security updates.

If you discover a security vulnerability in JEPA Real-Time Sentiment Analysis, please report it to us responsibly.

Please do NOT report security vulnerabilities through public GitHub issues.

Instead, please send an email to security@superinstance.github.io with:

• A description of the vulnerability
• Steps to reproduce the issue
• Any potential impact you've identified
• If possible, a suggested fix or mitigation

Once you've submitted a vulnerability report:

1. Acknowledgment: We will respond within 48 hours to acknowledge receipt
2. Investigation: We will investigate the issue and determine severity
3. Resolution: We will work on a fix and aim to release a patch within 7 days for critical issues
4. Disclosure: We will coordinate public disclosure with you

• Local processing: All sentiment analysis happens locally in the browser
• No external APIs: No text data is sent to external servers
• No telemetry: JEPA does not collect telemetry or usage data
• Private by design: Your text data remains completely private

• No storage: Text data is not stored by default
• Ephemeral processing: Data is processed and discarded
• User-controlled: Users control what text is analyzed
• No logging: Sensitive text is never logged

• Use HTTPS: Always load your application over HTTPS in production
• Content Security Policy: Implement strict CSP headers to prevent XSS attacks
• Validate inputs: Ensure text inputs are sanitized
• Secure model loading: Load models from trusted sources

JEPA is designed to work with zero configuration. For advanced usage:

# Optional: Enable debug mode (development only)
DEBUG_JEPA=true

# Optional: Custom model path
JEPA_MODEL_PATH=/custom/path/to/model

# Optional: WebGPU flags
JEPA_FORCE_CPU=false

• Regularly update dependencies: npm update
• Audit dependencies for vulnerabilities: npm audit
• Review security advisories for dependencies
• Keep Node.js updated to the latest stable version

• Validate all text inputs before processing
• Sanitize user-provided text
• Implement rate limiting for API usage
• Protect against memory exhaustion
• Limit text length to prevent DoS

• Input Validation: All text inputs are validated and sanitized
• Memory Safety: Proper memory management for large texts
• Dependency Auditing: Regular security audits of dependencies
• Type Safety: TypeScript strict mode catches many potential issues
• Browser Security: Leverages browser security model
• No External Requests: All analysis happens locally

• Local Processing: All sentiment analysis happens in the browser
• No Server Communication: Zero data transmission to external servers
• User Control: Users have full control over their data
• Offline Capable: Works completely offline after initial load
• Data Ownership: Text data belongs entirely to the user

• Model Security: Security depends on how models are loaded
• Memory Constraints: Large texts require significant memory
• Browser Compatibility: WebGPU support varies by browser
• Performance: Analysis speed depends on device capabilities
• Text Sensitivity: Users should avoid analyzing extremely sensitive text

This project has not yet undergone a formal security audit. We welcome contributions from security researchers and encourage responsible disclosure of any vulnerabilities found.

We actively monitor our dependencies for security vulnerabilities:

• Zero runtime dependencies
• Minimal development dependencies
• Regular npm audit checks
• Immediate action on high-severity vulnerabilities
• Automated Dependabot security updates

• Secure Context: WebGPU requires secure context (HTTPS)
• Permission Model: Respects browser permission requirements
• Resource Limits: Enforces GPU resource limits
• Isolated Processing: GPU operations are isolated
• Fallback Safety: Graceful fallback to CPU processing

• Trusted Sources: Load models from trusted sources only
• Validation: Validate model integrity before loading
• Sandboxed Execution: Models run in browser sandbox
• No Arbitrary Code: Models cannot execute arbitrary code
• Resource Limits: Enforce memory and computation limits

• No Persistence: Text data is not persisted by default
• Immediate Processing: Data is processed and immediately discarded
• User Control: Users control what text is analyzed
• No Logging: Text data is never logged or recorded
• Memory Clearing: Sensitive data is cleared from memory

When using JEPA for sentiment analysis:

• User Consent: Obtain consent before analyzing user-generated text
• Transparency: Be transparent about sentiment analysis usage
• Purpose Limitation: Use sentiment data for stated purposes only
• Data Minimization: Only analyze text that is necessary
• Privacy by Design: Design systems with privacy in mind

For security-related inquiries:

• Security Vulnerabilities: security@superinstance.github.io
• General Inquiries: support@superinstance.github.io

• Critical Vulnerabilities: 48 hours initial response, 7 days for fix
• High Severity: 72 hours initial response, 14 days for fix
• Medium Severity: 1 week initial response, 30 days for fix
• Low Severity: 2 weeks initial response, next release for fix

Thank you for helping keep JEPA Real-Time Sentiment Analysis and its users safe!