DevNinja AI Learning is committed to maintaining the security and privacy of our educational platform. This document outlines our security policies, vulnerability reporting procedures, and best practices for contributors.

We actively maintain security updates for the following versions:

As this is an early-stage educational platform, we currently support only the latest version. Security patches will be applied to the main branch and released promptly.

• Content Security Policy (CSP): Configured to prevent XSS attacks
• Security Headers: X-Frame-Options, X-Content-Type-Options, X-XSS-Protection
• Permissions Policy: Restricts access to sensitive browser APIs
• Strict Transport Security: HTTPS enforcement
• Input Sanitization: MDX content processing with secure defaults
• Dependency Scanning: Regular updates of npm packages

• No User Data Collection: The platform does not collect or store personal user data
• Static Content: Educational content is served statically without user-generated content
• Client-Side Processing: Simulations run entirely in the browser
• No Authentication: No user accounts or login systems currently implemented

If you discover a security vulnerability in DevNinja AI Learning, please report it responsibly:

DO NOT create a public GitHub issue for security vulnerabilities.

Instead, please:

1. Email: Send details to security@devninja.in
2. Subject Line: Use "Security Vulnerability Report - DevNinja AI Learning"
3. Include:
   • Description of the vulnerability
   • Steps to reproduce the issue
   • Potential impact assessment
   • Suggested remediation (if known)
   • Your contact information

• Acknowledgment: We will acknowledge receipt within 24 hours
• Initial Assessment: We will provide an initial assessment within 72 hours
• Resolution Timeline: Critical vulnerabilities will be addressed within 7 days
• Updates: Regular status updates will be provided every 72 hours until resolution
• Credit: Security researchers will be credited (unless anonymity is requested)

We follow a responsible disclosure process:

1. Private Disclosure: Report sent to security team
2. Acknowledgment: Security team confirms receipt and begins investigation
3. Assessment: Vulnerability is validated and impact assessed
4. Fix Development: Security patch is developed and tested
5. Release: Fix is released and security advisory published
6. Public Disclosure: Details published after users have had time to update

• XSS Prevention: Sanitize all user inputs and use React's built-in protections
• Component Security: Avoid dangerouslySetInnerHTML unless absolutely necessary
• Dependency Management: Keep dependencies updated and audit for vulnerabilities
• Content Security: Ensure MDX content follows security best practices

• Safe Examples: Code examples should demonstrate secure practices
• No Secrets: Never include API keys, tokens, or credentials in content
• External Links: Verify all external links point to reputable sources
• Safe Dependencies: Educational examples should use well-maintained libraries

• Environment Variables: Use proper environment variable handling
• Secure Headers: Maintain security header configurations
• Asset Security: Ensure static assets are served securely
• Build Security: Keep build tools and processes up to date

1. Code Review: All changes require security-focused code review
2. Dependency Audits: Regular npm audit checks before releases
3. Static Analysis: Automated security scanning in CI/CD pipeline
4. Testing: Security-focused testing for new features
5. Documentation: Security considerations documented for new features

• Client-Side Secrets: Never expose sensitive data in frontend code
• Unsafe External Content: Always validate and sanitize external content
• Insecure Dependencies: Avoid packages with known vulnerabilities
• Weak CSP: Don't weaken Content Security Policy without careful consideration
• Unsafe HTML: Avoid HTML injection vulnerabilities in educational content

• Primary Contact: security@devninja.in
• Emergency Contact: For critical vulnerabilities requiring immediate attention
• Response Time: 24 hours for acknowledgment, 72 hours for initial assessment
• Preferred Language: English

• Scope: This security policy covers the main DevNinja AI Learning platform
• Out of Scope: Third-party services, dependencies maintained by other projects
• Testing Guidelines: Please test against local instances, not production
• Recognition: Security researchers will be acknowledged in our security acknowledgments

• Safe Usage: The platform is designed for educational use with minimal security risks
• Privacy: No personal data is collected during normal platform usage
• Browser Security: Keep browsers updated for optimal security when using simulations
• Reporting Issues: Report any suspicious behavior or security concerns

• Notification Channels: Security updates will be announced via GitHub releases
• Severity Levels: Critical, High, Medium, Low based on CVSS scoring
• Update Process: Security patches will be released as soon as possible
• Changelog: Security fixes will be clearly marked in release notes

• Security Standards: Following OWASP Top 10 web application security guidelines
• Educational Standards: Ensuring security education examples follow best practices
• Open Source Security: Adhering to open source security best practices
• Regular Reviews: Periodic security reviews of the platform and its dependencies

We thank the security community for helping keep DevNinja AI Learning secure. Security researchers who responsibly report vulnerabilities will be acknowledged here:

• [Security researchers will be listed here upon reporting validated vulnerabilities]

Last Updated: April 20, 2026 Next Review: July 20, 2026

This security policy is reviewed and updated quarterly to ensure it remains current with best practices and project evolution.