implementing-api-gateway-security-controls

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

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-api-gateway-security-controls
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summary

Implements security controls at the API gateway layer including authentication enforcement, rate limiting, request validation, IP allowlisting, TLS termination, and threat protection. The engineer configures API gateways (Kong, AWS API Gateway, Azure APIM, Apigee) to act as a centralized security enforcement point that validates, throttles, and monitors all API traffic before it reaches backend services. Activates for requests involving API gateway security, API management security, gateway authentication, or centralized API protection.

skill.md
name
implementing-api-gateway-security-controls
description
'Implements security controls at the API gateway layer including authentication enforcement, rate limiting, request validation, IP allowlisting, TLS termination, and threat protection. The engineer configures API gateways (Kong, AWS API Gateway, Azure APIM, Apigee) to act as a centralized security enforcement point that validates, throttles, and monitors all API traffic before it reaches backend services. Activates for requests involving API gateway security, API management security, gateway authentication, or centralized API protection. '
domain
cybersecurity
subdomain
api-security
tags
- api-security - api-gateway - kong - aws-api-gateway - rate-limiting - waf
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
- PR.PS-01 - ID.RA-01 - PR.DS-10 - DE.CM-01

Implementing API Gateway Security Controls

When to Use

  • Deploying a centralized authentication and authorization layer for microservice APIs
  • Implementing rate limiting, throttling, and quota management across all API endpoints
  • Configuring request/response validation against OpenAPI specifications at the gateway level
  • Setting up TLS termination, mutual TLS, and certificate management for API traffic
  • Integrating WAF rules with the API gateway to block injection, XSS, and known attack patterns

Do not use as the sole security layer. API gateways provide defense in depth but backend services must also validate authorization and input.

Prerequisites

  • API gateway platform selected and deployed (Kong, AWS API Gateway, Azure APIM, or Apigee)
  • OpenAPI/Swagger specifications for all backend APIs
  • TLS certificates for the gateway domain
  • Identity provider (IdP) configured for OAuth2/OIDC (Okta, Auth0, Azure AD)
  • Monitoring and logging infrastructure (CloudWatch, Datadog, ELK)
  • Backend service endpoints registered and reachable from the gateway

Workflow

Step 1: Kong Gateway Security Configuration

# kong.yml - Declarative Kong configuration with security plugins
_format_version: "3.0"

services:
  - name: user-service
    url: http://user-service:8080
    routes:
      - name: user-api
        paths:
          - /api/v1/users
        methods:
          - GET
          - POST
          - PUT
          - PATCH
          - DELETE
        strip_path: false

plugins:
  # 1. Authentication: JWT validation
  - name: jwt
    config:
      uri_param_names:
        - jwt
      header_names:
        - Authorization
      claims_to_verify:
        - exp
      maximum_expiration: 3600  # Max 1 hour token TTL

  # 2. Rate Limiting
  - name: rate-limiting
    config:
      minute: 60
      hour: 1000
      policy: redis
      redis_host: redis
      redis_port: 6379
      fault_tolerant: true
      hide_client_headers: false
      limit_by: credential  # Per-user, not per-IP

  # 3. Request Size Limiting
  - name: request-size-limiting
    config:
      allowed_payload_size: 1  # 1 MB max
      size_unit: megabytes

  # 4. IP Restriction (admin endpoints)
  - name: ip-restriction
    service: admin-service
    config:
      allow:
        - 10.0.0.0/8
        - 172.16.0.0/12

  # 5. Bot Detection
  - name: bot-detection
    config:
      deny:
        - "sqlmap"
        - "nikto"
        - "nmap"
        - "masscan"

  # 6. CORS Configuration
  - name: cors
    config:
      origins:
        - "https://app.example.com"
      methods:
        - GET
        - POST
        - PUT
        - PATCH
        - DELETE
      headers:
        - Authorization
        - Content-Type
      credentials: true
      max_age: 3600

  # 7. Response Transformer - Remove sensitive headers
  - name: response-transformer
    config:
      remove:
        headers:
          - X-Powered-By
          - Server
      add:
        headers:
          - "X-Content-Type-Options: nosniff"
          - "X-Frame-Options: DENY"
          - "Strict-Transport-Security: max-age=31536000; includeSubDomains"
          - "Content-Security-Policy: default-src 'none'"

Step 2: AWS API Gateway Security Configuration

import boto3
import json

apigw = boto3.client('apigatewayv2')

# Create API with mutual TLS
api_response = apigw.create_api(
    Name='secure-api',
    ProtocolType='HTTP',
    DisableExecuteApiEndpoint=True,  # Force custom domain
)
api_id = api_response['ApiId']

# Configure authorizer (JWT with Cognito)
authorizer = apigw.create_authorizer(
    ApiId=api_id,
    AuthorizerType='JWT',
    IdentitySource='$request.header.Authorization',
    Name='cognito-jwt-authorizer',
    JwtConfiguration={
        'Audience': ['your-app-client-id'],
        'Issuer': 'https://cognito-idp.us-east-1.amazonaws.com/us-east-1_xxxxx'
    }
)

# Create route with authorizer
apigw.create_route(
    ApiId=api_id,
    RouteKey='GET /api/v1/users',
    AuthorizerId=authorizer['AuthorizerId'],
    AuthorizationType='JWT',
)

# Configure throttling
apigw.create_stage(
    ApiId=api_id,
    StageName='prod',
    DefaultRouteSettings={
        'ThrottlingBurstLimit': 100,
        'ThrottlingRateLimit': 50.0,  # 50 requests per second
    },
    AccessLogSettings={
        'DestinationArn': 'arn:aws:logs:us-east-1:123456789:log-group:api-access-logs',
        'Format': json.dumps({
            'requestId': '$context.requestId',
            'ip': '$context.identity.sourceIp',
            'caller': '$context.identity.caller',
            'user': '$context.identity.user',
            'requestTime': '$context.requestTime',
            'httpMethod': '$context.httpMethod',
            'resourcePath': '$context.resourcePath',
            'status': '$context.status',
            'protocol': '$context.protocol',
            'responseLength': '$context.responseLength'
        })
    }
)

# WAF association
waf = boto3.client('wafv2')
web_acl = waf.create_web_acl(
    Name='api-security-acl',
    Scope='REGIONAL',
    DefaultAction={'Allow': {}},
    Rules=[
        {
            'Name': 'AWS-AWSManagedRulesSQLiRuleSet',
            'Priority': 1,
            'Statement': {
                'ManagedRuleGroupStatement': {
                    'VendorName': 'AWS',
                    'Name': 'AWSManagedRulesSQLiRuleSet'
                }
            },
            'OverrideAction': {'None': {}},
            'VisibilityConfig': {
                'SampledRequestsEnabled': True,
                'CloudWatchMetricsEnabled': True,
                'MetricName': 'SQLiRuleSet'
            }
        },
        {
            'Name': 'RateLimit',
            'Priority': 2,
            'Statement': {
                'RateBasedStatement': {
                    'Limit': 2000,
                    'AggregateKeyType': 'IP'
                }
            },
            'Action': {'Block': {}},
            'VisibilityConfig': {
                'SampledRequestsEnabled': True,
                'CloudWatchMetricsEnabled': True,
                'MetricName': 'RateLimitRule'
            }
        },
    ],
    VisibilityConfig={
        'SampledRequestsEnabled': True,
        'CloudWatchMetricsEnabled': True,
        'MetricName': 'ApiSecurityACL'
    }
)

Step 3: Request Validation with OpenAPI Schema

# Kong OAS Validation Plugin configuration
plugins:
  - name: oas-validation
    config:
      api_spec: |
        openapi: "3.0.3"
        info:
          title: Secure API
          version: "1.0"
        paths:
          /api/v1/users:
            post:
              requestBody:
                required: true
                content:
                  application/json:
                    schema:
                      type: object
                      required: [name, email]
                      properties:
                        name:
                          type: string
                          maxLength: 100
                          pattern: "^[a-zA-Z ]+$"
                        email:
                          type: string
                          format: email
                          maxLength: 255
                      additionalProperties: false  # Block mass assignment
              responses:
                '201':
                  description: User created
      validate_request_body: true
      validate_request_header_params: true
      validate_request_query_params: true
      validate_request_uri_params: true
      verbose_response: false  # Do not expose schema details in errors

Step 4: Mutual TLS Configuration

# Generate CA and client certificates for mTLS
# 1. Create CA
openssl genrsa -out ca.key 4096
openssl req -new -x509 -key ca.key -out ca.crt -days 365 \
    -subj "/CN=API Gateway CA/O=Example Corp"

# 2. Create client certificate
openssl genrsa -out client.key 2048
openssl req -new -key client.key -out client.csr \
    -subj "/CN=api-client/O=Example Corp"
openssl x509 -req -in client.csr -CA ca.crt -CAkey ca.key \
    -CAcreateserial -out client.crt -days 365

# Kong mTLS configuration
# Upload CA certificate to Kong
curl -X POST http://kong-admin:8001/ca_certificates \
    -F "[email protected]"

# Enable mTLS plugin
curl -X POST http://kong-admin:8001/services/user-service/plugins \
    --data "name=mtls-auth" \
    --data "config.ca_certificates[]=$(cat ca_cert_id)" \
    --data "config.revocation_check_mode=SKIP" \
    --data "config.authenticated_group_by=CN"

Step 5: Logging and Monitoring Configuration

# CloudWatch monitoring for API security events
import boto3

cloudwatch = boto3.client('cloudwatch')
logs = boto3.client('logs')

# Create metric filters for security events
security_filters = [
    {
        'name': 'UnauthorizedAccess',
        'pattern': '{ $.status = 401 || $.status = 403 }',
        'metric': 'UnauthorizedAccessCount'
    },
    {
        'name': 'RateLimitHits',
        'pattern': '{ $.status = 429 }',
        'metric': 'RateLimitHitCount'
    },
    {
        'name': 'ServerErrors',
        'pattern': '{ $.status >= 500 }',
        'metric': 'ServerErrorCount'
    },
    {
        'name': 'LargeResponses',
        'pattern': '{ $.responseLength > 1000000 }',
        'metric': 'LargeResponseCount'
    },
]

for sf in security_filters:
    logs.put_metric_filter(
        logGroupName='api-access-logs',
        filterName=sf['name'],
        filterPattern=sf['pattern'],
        metricTransformations=[{
            'metricName': sf['metric'],
            'metricNamespace': 'APISecurityMetrics',
            'metricValue': '1',
            'defaultValue': 0
        }]
    )

# Create alarm for unusual 401/403 spike
cloudwatch.put_metric_alarm(
    AlarmName='API-UnauthorizedAccessSpike',
    MetricName='UnauthorizedAccessCount',
    Namespace='APISecurityMetrics',
    Statistic='Sum',
    Period=300,  # 5 minutes
    EvaluationPeriods=1,
    Threshold=100,
    ComparisonOperator='GreaterThanThreshold',
    AlarmActions=['arn:aws:sns:us-east-1:123456789:security-alerts'],
    AlarmDescription='More than 100 unauthorized access attempts in 5 minutes'
)

Key Concepts

TermDefinition
API GatewayCentralized entry point for all API traffic that enforces authentication, authorization, rate limiting, and request validation before routing to backend services
Rate LimitingControlling the number of API requests per client within a time window to prevent abuse and ensure fair resource allocation
Request ValidationVerifying that incoming API requests conform to the expected schema (data types, required fields, value ranges) before forwarding to backend services
Mutual TLS (mTLS)Two-way TLS authentication where both the client and server present certificates, providing strong identity verification for API-to-API communication
WAF IntegrationWeb Application Firewall rules applied at the API gateway to block common attack patterns (SQLi, XSS, path traversal)
OAuth2/OIDCToken-based authentication protocols where the gateway validates JWT tokens against an identity provider before allowing access

Tools & Systems

  • Kong Gateway: Open-source API gateway with extensive plugin ecosystem for security, rate limiting, and authentication
  • AWS API Gateway: Managed API gateway service with built-in throttling, WAF integration, and Lambda authorizers
  • Azure API Management: Enterprise API gateway with policy-based security, developer portal, and Azure AD integration
  • Apigee (Google Cloud): API management platform with threat protection, quota management, and API analytics
  • Envoy Proxy: High-performance proxy used as API gateway in service mesh architectures with extensive filter chain

Common Scenarios

Scenario: Securing a Microservice API with Kong Gateway

Context: A company is migrating from a monolithic API to microservices. Each microservice has its own REST API. The security team needs to implement centralized authentication, rate limiting, and request validation without modifying each service.

Approach:

  1. Deploy Kong Gateway as the single entry point, routing traffic to 8 backend microservices
  2. Configure JWT validation plugin to verify tokens against the company's Keycloak IdP
  3. Apply rate limiting: 60 requests/minute for regular users, 300/minute for premium users, identified by JWT claims
  4. Enable OAS validation plugin to reject requests that do not match the OpenAPI spec (blocks mass assignment and injection)
  5. Configure mTLS for service-to-service communication behind the gateway
  6. Set up response transformer to remove Server and X-Powered-By headers and add security headers
  7. Integrate with AWS WAF for SQL injection and XSS protection rules
  8. Configure access logging to CloudWatch with security metric filters and alerting

Pitfalls:

  • Relying solely on the gateway for authorization when backend services also need to verify permissions
  • Not configuring rate limiting per authenticated user (per-IP only allows attackers to bypass with IP rotation)
  • Using verbose error responses from the gateway that reveal internal service architecture
  • Not testing the gateway configuration with security tools after deployment
  • Missing mutual TLS between the gateway and backend services, allowing direct backend access

Output Format

## API Gateway Security Configuration Report

**Gateway**: Kong 3.5 (Kubernetes deployment)
**Backend Services**: 8 microservices
**Date**: 2024-12-15

### Security Controls Implemented

| Control | Plugin/Feature | Configuration |
|---------|---------------|---------------|
| Authentication | JWT Plugin | Cognito IdP, 1-hour max TTL |
| Rate Limiting | Rate Limiting Plugin | 60 req/min (user), Redis-backed |
| Request Validation | OAS Validation | Strict mode, no additional properties |
| TLS | Kong TLS | TLS 1.3 only, HSTS enabled |
| mTLS | mTLS Auth Plugin | Client cert required for admin APIs |
| WAF | AWS WAF | SQLi, XSS, rate-based rules |
| Headers | Response Transformer | Server header removed, security headers added |
| Logging | HTTP Log Plugin | CloudWatch, security metric filters |

### Verification Results

- JWT validation: Expired/invalid tokens correctly rejected (tested 50 payloads)
- Rate limiting: Enforced at 60 req/min, 429 returned with Retry-After header
- Request validation: Malformed requests rejected with 400 (tested 30 invalid payloads)
- mTLS: Requests without client certificate rejected with 401
- WAF: SQL injection payloads blocked (tested top 100 SQLi patterns)
how to use implementing-api-gateway-security-controls

How to use implementing-api-gateway-security-controls on Cursor

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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-gateway-security-controls
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-gateway-security-controls

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

3

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Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-api-gateway-security-controls

Reload or restart Cursor to activate implementing-api-gateway-security-controls. Access the skill through slash commands (e.g., /implementing-api-gateway-security-controls) or your agent's skill management interface.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

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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

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general reviews

Ratings

4.638 reviews
  • Kofi Jain· Dec 28, 2024

    implementing-api-gateway-security-controls has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ira Khan· Dec 24, 2024

    implementing-api-gateway-security-controls is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Isabella Okafor· Dec 16, 2024

    Solid pick for teams standardizing on skills: implementing-api-gateway-security-controls is focused, and the summary matches what you get after install.

  • Amina Bhatia· Dec 8, 2024

    implementing-api-gateway-security-controls reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Kapoor· Nov 27, 2024

    I recommend implementing-api-gateway-security-controls for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diya Ghosh· Nov 15, 2024

    implementing-api-gateway-security-controls fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Naina Sharma· Oct 18, 2024

    Useful defaults in implementing-api-gateway-security-controls — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ren Shah· Oct 6, 2024

    We added implementing-api-gateway-security-controls from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Meera Anderson· Sep 25, 2024

    Useful defaults in implementing-api-gateway-security-controls — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Sep 21, 2024

    Registry listing for implementing-api-gateway-security-controls matched our evaluation — installs cleanly and behaves as described in the markdown.

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