Comprehensive security checklist for API endpoint development. Ensures proper authentication, authorization, input validation, output safety, and security logging are implemented before deployment.
Fetches api-security-review from bobmatnyc/claude-mpm-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/api-security-review
Restart Cursor to activate api-security-review. Access via /api-security-review in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Comprehensive security checklist for API endpoint development. Ensures proper authentication, authorization, input validation, output safety, and security logging are implemented before deployment.
When to Use
Before merging any PR with API changes
When creating new API endpoints
When modifying authentication/authorization logic
During security audits
Code review of API routes
Quick Checklist
Pre-Deployment Security Audit
Authentication: Route requires valid user identity
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")asyncdefget_current_user(token:str= Depends(oauth2_scheme)): user =await verify_token(token)ifnot user:raise HTTPException( status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid authentication credentials", headers={"WWW-Authenticate":"Bearer"},)return user
@app.get("/api/protected")asyncdefprotected_route(current_user: User = Depends(get_current_user)):return{"user": current_user.email}
Django REST Framework
from rest_framework.decorators import api_view, permission_classes
from rest_framework.permissions import IsAuthenticated
from rest_framework.response import Response
@api_view(['GET'])@permission_classes([IsAuthenticated])defprotected_view(request):# request.user is authenticatedreturn Response({'user': request.user.email})
Authorization
Resource Ownership Verification
Authentication proves WHO the user is. Authorization proves the user has permission to access the resource.
›Claude Desktop or compatible AI client with skill support
›Clear understanding of task or problem to solve
›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
1Install skill using provided installation command
2Test with simple use case relevant to your work
3Evaluate output quality and relevance
4Iterate on prompts to improve results
5Integrate into regular workflow if valuable
Common Pitfalls
⚠Expecting perfect results without iteration
⚠Not providing enough context in prompts
⚠Using skill for tasks outside its intended scope
⚠Accepting outputs without review and validation
Best Practices
✓ Do
+Start with clear, specific prompts
+Provide relevant context and constraints
+Review and refine all outputs before using
+Iterate to improve output quality
+Document successful prompt patterns
✗ Don't
−Don't use without understanding skill limitations
−Don't skip validation of outputs
−Don't share sensitive information in prompts
−Don't expect skill to replace human judgment
💡 Pro Tips
★Be specific about desired format and style
★Ask for multiple options to choose from
★Request explanations to understand reasoning
★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
1Familiarize yourself with skill capabilities and limitations
2Start with low-risk, non-critical tasks
3Progress to more complex and valuable use cases
4Build expertise through regular use and experimentation
