The AI Chatbot Exploitation Lab is an educational platform designed to teach AI security concepts through controlled, hands-on experience. While this project intentionally contains vulnerable components for educational purposes, we take the security of the platform itself very seriously.

This security policy covers:

• Platform Security: The underlying infrastructure and application security
• Educational Content: Responsible disclosure of educational vulnerabilities
• User Data Protection: Privacy and data handling practices
• Deployment Security: Secure deployment and configuration practices

The following vulnerabilities are intentionally included for educational purposes:

• AI Prompt Injection: Social engineering attacks against the chatbot
• Privilege Escalation: Simulated admin access through social engineering
• Command Execution: Limited command execution in sandboxed environment
• Credential Exposure: Planted AWS credentials in sandbox environment

These are not security issues and should not be reported as vulnerabilities.

Please report these types of actual security vulnerabilities:

• Authentication Bypass: Unauthorized access to admin functions
• Sandbox Escape: Breaking out of the controlled environment
• Data Exposure: Exposure of real user data or system information
• Code Injection: Actual code execution outside the sandbox
• Infrastructure Issues: Database, or server vulnerabilities
• Dependency Vulnerabilities: Security issues in third-party packages

We provide security updates for the following versions:

If you discover a legitimate security vulnerability in the platform infrastructure:

1. DO NOT create a public GitHub issue
2. DO NOT discuss the vulnerability publicly
3. DO report it privately using one of these methods:

1. GitHub Security Advisories (Recommended):

   • Go to the repository's Security tab
   • Click "Report a vulnerability"
   • Fill out the private vulnerability report form

2. Email (Alternative):

   • Send details to: security@[project-domain]
   • Use PGP encryption if possible (key available on request)
   • Include "SECURITY VULNERABILITY" in the subject line

Please provide the following information:

• Vulnerability Type: What kind of security issue is it?
• Impact Assessment: What could an attacker accomplish?
• Affected Components: Which parts of the system are affected?
• Reproduction Steps: Clear steps to reproduce the issue
• Proof of Concept: Code or screenshots demonstrating the issue
• Suggested Fix: If you have ideas for remediation
• Disclosure Timeline: Your preferred timeline for public disclosure

If you find issues with the educational vulnerabilities or content:

1. Create a public GitHub issue with the label educational
2. Describe the educational impact of the issue
3. Suggest improvements to the learning experience
4. Consider the learning objectives when proposing changes

• Acknowledgment: We will acknowledge receipt within 48 hours
• Initial Assessment: We will provide an initial assessment within 7 business days
• Regular Updates: We will provide updates regularly during investigation

1. Verification: Confirm the vulnerability exists
2. Impact Assessment: Evaluate the severity and scope
3. Fix Development: Develop and test a fix
4. Security Review: Conduct thorough security review
5. Deployment Planning: Plan secure deployment of fixes

We use the following severity levels:

• Immediate threat to user data or system integrity
• Remote code execution with high privileges
• Complete system compromise possible
• Response Time: Within 24 hours

• Significant security impact
• Privilege escalation or data exposure
• Authentication bypass
• Response Time: Within 72 hours

• Moderate security impact
• Limited data exposure
• Denial of service vulnerabilities
• Response Time: Within 1 week

• Minor security impact
• Information disclosure
• Configuration issues
• Response Time: Within 2 weeks

We follow responsible disclosure practices:

1. Day 0: Vulnerability reported
2. Day 1-2: Acknowledgment sent
3. Day 3-7: Initial assessment completed
4. Day 8-30: Fix development and testing
5. Day 31-45: Fix deployment and verification
6. Day 46-90: Public disclosure (coordinated with reporter)

After fixes are deployed:

• Security Advisory: Published on GitHub Security Advisories
• Release Notes: Included in next release notes
• Credit: Reporter credited (if desired)
• CVE Assignment: If applicable, CVE will be requested

When contributing to this project:

1. Input Validation: Always validate and sanitize user inputs
2. Authentication: Implement proper authentication mechanisms
3. Authorization: Ensure appropriate access controls
4. Logging: Log security events appropriately
5. Dependencies: Keep dependencies updated and secure
6. Secrets: Never commit secrets, API keys, or credentials
7. Testing: Include security tests for new features

When deploying this application:

1. Environment Variables: Secure all environment variables
2. Network Security: Use appropriate firewall rules
3. HTTPS: Always use HTTPS in production
4. Updates: Keep the application and dependencies updated
5. Monitoring: Implement security monitoring and alerting
6. Backups: Maintain secure backups of data
7. Access Control: Limit administrative access

When using this educational platform:

1. Isolated Environment: Deploy in isolated/sandboxed environments
2. No Real Data: Never use real credentials or sensitive data
3. Network Isolation: Consider network isolation for training
4. Regular Updates: Keep the platform updated
5. Responsible Use: Use only for educational purposes

The platform includes several security controls:

1. Input Sanitization: All user inputs are sanitized
2. Rate Limiting: Prevents abuse and DoS attacks
3. Command Whitelisting: Only specific commands allowed
4. Path Restrictions: File access limited to sandbox
5. Session Management: Secure session handling
6. Logging: Comprehensive security event logging
7. Brute Force Protection: Progressive delays and blocking

The command execution environment is sandboxed:

• Isolated File System: Separate from host system
• Limited Commands: Only cat, ls, and more allowed
• Path Restrictions: Access limited to /home/ directory
• No Network Access: Sandbox has no external network access
• Resource Limits: CPU and memory limits enforced

This project follows:

• OWASP Top 10: Web application security risks
• NIST Cybersecurity Framework: Security best practices
• Secure Coding Practices: Industry-standard secure coding
• Privacy by Design: Privacy-focused development

For educational content:

• Ethical Guidelines: Responsible security education
• Legal Compliance: Compliance with applicable laws
• Academic Standards: Appropriate for educational use
• Accessibility: Accessible to diverse learners

• OWASP Web Security Testing Guide
• NIST Cybersecurity Framework
• Secure Coding Practices

• Static Analysis: ESLint security rules, Semgrep
• Dependency Scanning: npm audit, Snyk
• Container Scanning: Docker security scanning
• Dynamic Testing: OWASP ZAP, Burp Suite

• Primary Contact: security@[project-domain]
• Backup Contact: admin@[project-domain]
• PGP Key: Available on request

For critical security issues requiring immediate attention:

• Email: urgent-security@[project-domain]
• Response Time: Within 4 hours during business hours

We support security research conducted in good faith and will not pursue legal action against researchers who:

• Follow responsible disclosure practices
• Do not access or modify user data
• Do not perform testing that could harm the service
• Do not violate any applicable laws or regulations

This security policy applies only to:

• The official AI Chatbot Exploitation Lab repository
• Official deployments and distributions
• Educational content and materials

It does not cover:

• Third-party deployments or modifications
• User-generated content or configurations
• External dependencies (report to respective maintainers)

We thank the security research community for helping keep this educational platform secure.

Remember: This is an educational platform designed to teach security concepts. The intentional vulnerabilities are for learning purposes only and should never be used maliciously or against systems without explicit permission.