We take the security of Canvas MCP seriously. If you discover a security vulnerability, please follow these guidelines:

DO NOT open a public GitHub issue for security vulnerabilities. Instead:

1. Email: Send details to the maintainer at the email listed in the repository
2. GitHub Security Advisory: Use GitHub's Security Advisory feature (preferred)

Please provide:

• Description of the vulnerability
• Steps to reproduce
• Potential impact
• Suggested fix (if available)

• Initial Response: Within 48 hours
• Status Update: Within 7 days
• Fix Timeline: Varies based on severity
  • Critical: 1-7 days
  • High: 7-14 days
  • Medium: 14-30 days
  • Low: Best effort

Critical: Your Canvas API token has full access to your Canvas account

1. Never commit tokens to version control

   • Always use .env file for token storage
   • Verify .env is in .gitignore
   • Use the provided env.template as a starting point

2. Token Storage

   • Store tokens in .env file with restricted permissions (chmod 600 .env)
   • Never share tokens via email, chat, or screenshots
   • Use environment-specific tokens (dev vs. production)

3. Token Rotation

   • Rotate tokens periodically (recommended: every 90 days)
   • Immediately rotate if token may have been exposed
   • Revoke tokens when no longer needed

4. Access Scope

   • Canvas tokens have full account access - there is no scope limitation
   • Consider using a dedicated Canvas account with limited permissions for MCP operations
   • Never use admin account tokens unless absolutely necessary

The Canvas MCP server includes code execution capabilities (execute_typescript tool) for advanced operations.

Important Security Considerations:

1. Review Generated Code

   • Always review TypeScript code before execution
   • Understand what the code will do with your Canvas data
   • Be cautious of code that modifies grades, enrollments, or course settings

2. Execution Environment

   • Code executes locally in isolated temporary files
   • Temporary files are automatically deleted after execution
   • Environment variables are isolated (your Canvas token is still accessible)

3. Timeout Protection

   • Code execution has a 120-second timeout by default
   • Long-running operations are automatically terminated

4. What Code Execution Can Access

   • Your Canvas API token (via environment variables)
   • Your Canvas instance (via API calls)
   • Local filesystem (temporary directory only)
   • Network (can make HTTP requests)

Canvas MCP includes built-in privacy features for educational data:

1. Data Anonymization

   • Enable via ENABLE_DATA_ANONYMIZATION=true in .env
   • Anonymizes student names and emails before AI processing
   • Preserves student IDs for functional operations
   • Required for FERPA compliance when using AI tools

2. What Gets Anonymized

   • Student names → Generic identifiers (Student A, Student B, etc.)
   • Student emails → Anonymized addresses
   • Student IDs → Preserved (needed for Canvas operations)

3. What Does NOT Get Anonymized

   • Course information
   • Assignment titles and descriptions
   • Your own profile information
   • Submission content and grades (but student identifiers are anonymized)

1. HTTPS Only

   • Canvas API requires HTTPS
   • HTTP URLs are automatically upgraded to HTTPS

2. User-Agent Header

   • Canvas MCP includes proper User-Agent identification
   • Required by Canvas API (effective January 2026)
   • Format: canvas-mcp/{version} (repository-url)

3. Rate Limiting

   • Canvas API rate limits: ~700 requests per 10 minutes
   • Canvas MCP includes automatic retry with exponential backoff
   • Use max_concurrent=5 for bulk operations to avoid rate limits

1. Environment Isolation

   • Run Canvas MCP in isolated environments (containers, virtual machines)
   • Avoid running on shared systems with untrusted users
   • Use separate Canvas tokens for different environments

2. File Permissions

   • Restrict access to configuration files: chmod 600 .env
   • Ensure code execution directory has appropriate permissions
   • Review generated code files in code_api/ directory

3. Logging and Monitoring

   • Enable API request logging for debugging: LOG_API_REQUESTS=true
   • Monitor for unusual API activity
   • Review error logs for security issues

Canvas MCP includes several security features:

1. Automatic Rate Limit Handling

   • Exponential backoff on 429 errors
   • Configurable retry limits
   • Respects Canvas Retry-After headers

2. Timeout Protection

   • API request timeouts (configurable)
   • Code execution timeouts (120s default)
   • Prevents infinite loops and hangs

3. Input Validation

   • Type validation for all tool parameters
   • Course ID validation and caching
   • Parameter sanitization

4. Error Handling

   • Graceful error responses (no stack traces to users)
   • Detailed error logging for debugging
   • No sensitive data in error messages

5. Privacy Protection

   • Configurable data anonymization
   • Student PII protection
   • FERPA-compliant operation mode

1. No Authentication

   • MCP server trusts the local environment
   • No built-in authentication for MCP clients
   • Relies on Canvas API token for authorization

2. Code Execution Risks

   • execute_typescript tool executes arbitrary code
   • No sandboxing beyond temporary file isolation
   • User responsible for reviewing generated code

3. No Rate Limiting Control

   • Cannot prevent aggressive API usage
   • Relies on Canvas server-side rate limiting
   • User responsible for bulk operation throttling

4. Token Scope

   • Canvas API tokens have full account access
   • No way to limit token permissions via Canvas MCP
   • Use Canvas account permissions for access control

Future security enhancements under consideration:

• Optional MCP client authentication
• Code execution sandboxing (Docker/VM isolation)
• Token encryption at rest
• Audit logging for sensitive operations
• Rate limiting controls for bulk operations
• Granular operation permissions
• Security scanning for generated code

Canvas MCP can be configured for FERPA compliance:

1. Enable data anonymization: ENABLE_DATA_ANONYMIZATION=true
2. Review privacy settings before using AI tools
3. Ensure your Canvas instance is FERPA-compliant
4. Follow your institution's data handling policies

Users must comply with:

• Canvas API Terms of Service
• Your Canvas instance's acceptable use policy
• Your institution's data handling requirements

For security concerns:

• GitHub Security Advisory: Create Advisory (preferred)
• Email: See repository contact information

Please do not open public issues for security vulnerabilities.

Last Updated: December 2025