implementing-api-schema-validation-security

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-api-schema-validation-security
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summary

Implement API schema validation using OpenAPI specifications and JSON Schema to enforce input/output contracts and prevent injection, data exposure, and mass assignment attacks.

skill.md
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-PatternRiskFix
additionalProperties: true or missingMass assignmentSet additionalProperties: false
No maxLength on stringsBuffer overflow, DoSAdd appropriate maxLength constraints
No pattern on string fieldsInjection attacksAdd regex patterns to restrict input
No enum for fixed-value fieldsUnexpected input processingUse enum for fields with known values
format: password without TLSCredential exposureEnforce HTTPS-only server URLs
Missing error response schemasInformation leakageDefine all 4xx/5xx response schemas
readOnly fields in request bodyData manipulationEnforce readOnly server-side

References

how to use implementing-api-schema-validation-security

How to use implementing-api-schema-validation-security on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-api-schema-validation-security

The skills CLI fetches implementing-api-schema-validation-security from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-api-schema-validation-security

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.

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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. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.534 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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