implementing-api-schema-validation-security▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Implement API schema validation using OpenAPI specifications and JSON Schema to enforce input/output contracts and prevent injection, data exposure, and mass assignment attacks.
| name | implementing-api-schema-validation-security |
| description | Implement API schema validation using OpenAPI specifications and JSON Schema to enforce input/output contracts and prevent injection, data exposure, and mass assignment attacks. |
| domain | cybersecurity |
| subdomain | api-security |
| tags | - api-security - schema-validation - openapi - json-schema - input-validation - data-leakage-prevention - mass-assignment - api-gateway |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - ID.RA-01 - PR.DS-10 - DE.CM-01 |
Implementing API Schema Validation Security
Overview
API schema validation enforces that all data exchanged through APIs conforms to a predefined structure defined in OpenAPI Specification (OAS) or JSON Schema documents. This prevents injection attacks (SQLi, XSS, XXE), blocks mass assignment by rejecting unknown properties, prevents data leakage by validating response schemas, and ensures type safety across all API interactions. Schema validation operates at both the API gateway level (runtime enforcement) and during development (shift-left security).
When to Use
- When deploying or configuring implementing api schema validation security capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- OpenAPI Specification v3.0 or v3.1 for all API endpoints
- API gateway with schema validation support (Cloudflare API Shield, Kong, AWS API Gateway)
- JSON Schema draft-07 or later understanding
- Development environment with OpenAPI validation libraries
- CI/CD pipeline for automated schema compliance testing
Core Implementation
OpenAPI Schema with Security Constraints
openapi: 3.1.0
info:
title: Secure E-Commerce API
version: 2.0.0
servers:
- url: https://api.example.com/v2
description: Production (HTTPS enforced)
security:
- OAuth2:
- read:products
- write:orders
paths:
/products:
post:
operationId: createProduct
security:
- OAuth2: [write:products]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProductCreate'
responses:
'201':
description: Product created
content:
application/json:
schema:
$ref: '#/components/schemas/Product'
'400':
$ref: '#/components/responses/ValidationError'
'401':
$ref: '#/components/responses/Unauthorized'
/products/{productId}:
get:
operationId: getProduct
parameters:
- name: productId
in: path
required: true
schema:
type: string
format: uuid
pattern: '^[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$'
responses:
'200':
content:
application/json:
schema:
$ref: '#/components/schemas/Product'
components:
schemas:
ProductCreate:
type: object
required: [name, price, category]
properties:
name:
type: string
minLength: 1
maxLength: 200
pattern: '^[a-zA-Z0-9\s\-\.]+$' # No special chars for injection prevention
description:
type: string
maxLength: 2000
# Sanitize HTML entities
price:
type: number
format: float
minimum: 0.01
maximum: 999999.99
exclusiveMinimum: 0
category:
type: string
enum: [electronics, clothing, food, furniture, other]
tags:
type: array
items:
type: string
maxLength: 50
pattern: '^[a-zA-Z0-9\-]+$'
maxItems: 10
uniqueItems: true
additionalProperties: false # CRITICAL: Prevents mass assignment
Product:
type: object
required: [id, name, price]
properties:
id:
type: string
format: uuid
readOnly: true
name:
type: string
price:
type: number
category:
type: string
tags:
type: array
items:
type: string
createdAt:
type: string
format: date-time
readOnly: true
additionalProperties: false # Prevents data leakage of internal fields
ValidationErrorResponse:
type: object
required: [code, message]
properties:
code:
type: string
enum: [VALIDATION_ERROR]
message:
type: string
maxLength: 500
details:
type: array
items:
type: object
properties:
field:
type: string
error:
type: string
additionalProperties: false
maxItems: 50
additionalProperties: false
responses:
ValidationError:
description: Request validation failed
content:
application/json:
schema:
$ref: '#/components/schemas/ValidationErrorResponse'
Unauthorized:
description: Authentication required
securitySchemes:
OAuth2:
type: oauth2
flows:
authorizationCode:
authorizationUrl: https://auth.example.com/authorize
tokenUrl: https://auth.example.com/token
scopes:
read:products: Read product data
write:products: Create and update products
write:orders: Create orders
Server-Side Schema Validation (Python/FastAPI)
"""API Schema Validation Middleware for FastAPI
Enforces strict schema validation on all request and response payloads
to prevent injection, mass assignment, and data leakage attacks.
"""
from fastapi import FastAPI, Request, Response, HTTPException
from fastapi.middleware import Middleware
from pydantic import BaseModel, Field, field_validator, ConfigDict
from typing import List, Optional
import re
import json
from starlette.middleware.base import BaseHTTPMiddleware
app = FastAPI()
# Strict Pydantic models with security constraints
class ProductCreate(BaseModel):
model_config = ConfigDict(extra='forbid') # Reject unknown fields (mass assignment)
name: str = Field(min_length=1, max_length=200, pattern=r'^[a-zA-Z0-9\s\-\.]+$')
description: Optional[str] = Field(default=None, max_length=2000)
price: float = Field(gt=0, le=999999.99)
category: str = Field(pattern=r'^(electronics|clothing|food|furniture|other)$')
tags: Optional[List[str]] = Field(default=None, max_length=10)
@field_validator('name')
@classmethod
def sanitize_name(cls, v):
# Prevent XSS via HTML entities
dangerous_patterns = ['<script', 'javascript:', 'onerror=', 'onload=']
lower_v = v.lower()
for pattern in dangerous_patterns:
if pattern in lower_v:
raise ValueError(f'Invalid characters in name')
return v
@field_validator('description')
@classmethod
def sanitize_description(cls, v):
if v is None:
return v
# Strip potential SQL injection patterns
sql_patterns = [
r"('|--|;|/\*|\*/|xp_|exec\s|union\s+select|drop\s+table)",
]
for pattern in sql_patterns:
if re.search(pattern, v, re.IGNORECASE):
raise ValueError('Invalid content in description')
return v
@field_validator('tags')
@classmethod
def validate_tags(cls, v):
if v is None:
return v
if len(v) > 10:
raise ValueError('Maximum 10 tags allowed')
for tag in v:
if not re.match(r'^[a-zA-Z0-9\-]+$', tag) or len(tag) > 50:
raise ValueError(f'Invalid tag format: {tag}')
return v
class ProductResponse(BaseModel):
"""Response model that explicitly defines allowed output fields.
Prevents leakage of internal fields like internal_notes, cost_price, etc."""
model_config = ConfigDict(extra='forbid')
id: str
name: str
price: float
category: str
tags: List[str] = []
created_at: str
class ResponseValidationMiddleware(BaseHTTPMiddleware):
"""Middleware to validate response payloads against schema.
Prevents accidental data leakage by checking response content."""
SCHEMA_MAP = {
'/api/v2/products': {
'POST': {'response_model': ProductResponse},
'GET': {'response_model': ProductResponse},
}
}
async def dispatch(self, request: Request, call_next):
response = await call_next(request)
# Only validate JSON responses
content_type = response.headers.get('content-type', '')
if 'application/json' not in content_type:
return response
# Check if endpoint has a registered response schema
path = request.url.path
method = request.method
route_config = self.SCHEMA_MAP.get(path, {}).get(method)
if not route_config:
return response
# Read and validate response body
body = b""
async for chunk in response.body_iterator:
body += chunk
try:
data = json.loads(body)
model = route_config['response_model']
if isinstance(data, list):
for item in data:
model.model_validate(item)
else:
model.model_validate(data)
except Exception as e:
# Log the validation failure for security monitoring
print(f"SECURITY: Response schema violation on {method} {path}: {e}")
# Return a safe error instead of potentially leaked data
return Response(
content=json.dumps({"error": "Internal server error"}),
status_code=500,
media_type="application/json"
)
return Response(
content=body,
status_code=response.status_code,
headers=dict(response.headers),
media_type=response.media_type
)
app.add_middleware(ResponseValidationMiddleware)
@app.post("/api/v2/products", response_model=ProductResponse, status_code=201)
async def create_product(product: ProductCreate):
# ProductCreate model with extra='forbid' automatically rejects
# any unknown fields, preventing mass assignment attacks
# (e.g., attacker trying to set is_admin=true or price=0)
pass
Cloudflare API Shield Schema Validation
# Upload OpenAPI schema to Cloudflare API Shield
curl -X POST "https://api.cloudflare.com/client/v4/zones/{zone_id}/api_gateway/user_schemas" \
-H "Authorization: Bearer ${CF_API_TOKEN}" \
-H "Content-Type: multipart/form-data" \
-F "[email protected]" \
-F "kind=openapi_v3"
# Enable schema validation with blocking mode
curl -X PATCH "https://api.cloudflare.com/client/v4/zones/{zone_id}/api_gateway/settings/schema_validation" \
-H "Authorization: Bearer ${CF_API_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"validation_default_mitigation_action": "block",
"validation_override_mitigation_action": null
}'
CI/CD Schema Compliance Testing
# GitHub Actions workflow for schema validation in CI
name: API Schema Security Check
on:
pull_request:
paths: ['api/**', 'openapi/**']
jobs:
schema-security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Validate OpenAPI Schema
run: |
npm install -g @stoplight/spectral-cli
spectral lint openapi.yaml --ruleset .spectral-security.yaml
- name: Check for Security Anti-Patterns
run: |
python3 scripts/schema_security_check.py openapi.yaml
- name: Run Contract Tests
run: |
npm install -g dredd
dredd openapi.yaml http://localhost:3000 --hookfiles=./test/hooks.js
Security Anti-Patterns to Detect
| Anti-Pattern | Risk | Fix |
|---|---|---|
additionalProperties: true or missing | Mass assignment | Set additionalProperties: false |
No maxLength on strings | Buffer overflow, DoS | Add appropriate maxLength constraints |
No pattern on string fields | Injection attacks | Add regex patterns to restrict input |
No enum for fixed-value fields | Unexpected input processing | Use enum for fields with known values |
format: password without TLS | Credential exposure | Enforce HTTPS-only server URLs |
| Missing error response schemas | Information leakage | Define all 4xx/5xx response schemas |
readOnly fields in request body | Data manipulation | Enforce readOnly server-side |
References
- OpenAPI Specification v3.1: https://spec.openapis.org/oas/v3.1.0
- Cloudflare API Shield Schema Validation: https://developers.cloudflare.com/api-shield/security/schema-validation/
- Redocly API Security by Design: https://redocly.com/learn/security
- Impart Security API Validation: https://www.impart.ai/blog/detect-and-fix-api-vulnerabilities-using-validation-secure-principles-and-real-time-response
- OWASP API Security Top 10 2023: https://owasp.org/API-Security/editions/2023/en/0x00-header/
How to use implementing-api-schema-validation-security on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add implementing-api-schema-validation-security
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches implementing-api-schema-validation-security from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate implementing-api-schema-validation-security. Access the skill through slash commands (e.g., /implementing-api-schema-validation-security) or your agent's skill management interface.
Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›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
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★34 reviews- ★★★★★Yuki Martin· Dec 28, 2024
Registry listing for implementing-api-schema-validation-security matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yusuf Ghosh· Dec 28, 2024
Solid pick for teams standardizing on skills: implementing-api-schema-validation-security is focused, and the summary matches what you get after install.
- ★★★★★Yuki Gonzalez· Dec 12, 2024
implementing-api-schema-validation-security is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dhruvi Jain· Dec 8, 2024
implementing-api-schema-validation-security reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Emma Desai· Dec 8, 2024
implementing-api-schema-validation-security has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Oshnikdeep· Nov 27, 2024
I recommend implementing-api-schema-validation-security for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yuki Yang· Nov 19, 2024
Useful defaults in implementing-api-schema-validation-security — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yusuf Mehta· Nov 3, 2024
implementing-api-schema-validation-security fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Noor Mensah· Oct 22, 2024
We added implementing-api-schema-validation-security from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ganesh Mohane· Oct 18, 2024
Useful defaults in implementing-api-schema-validation-security — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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