API Rate Limiting Scanner
Evaluates API rate limiting implementation and bypass techniques.
What is API Rate Limiting?
API Rate Limiting testing evaluates how effectively an API limits request frequency. It tests for bypass techniques including distributed requests, endpoint enumeration, header manipulation, and logic flaws that allow exceeding intended limits for brute force, scraping, or denial of service.
Why is This Important?
Rate limiting protects against brute force attacks, credential stuffing, data scraping, and DoS. Weak rate limiting enables account takeover attempts, mass data extraction, and service disruption. Many APIs have rate limits that can be trivially bypassed.
How It Works
1. API Discovery
Automatically discovers API endpoints, methods, parameters, and authentication mechanisms from documentation or traffic.
2. Security Testing
Tests for OWASP API Top 10 vulnerabilities including broken authentication, excessive data exposure, and injection flaws.
3. Compliance Validation
Validates API security against industry standards with detailed findings and remediation guidance.
Key Capabilities
Complete API security coverage aligned with OWASP API Security Top 10 and industry best practices.
- Automatic API endpoint discovery
- Authentication and authorization testing
- Rate limiting and resource exhaustion checks
- Data exposure and sensitive info detection
- API versioning and deprecation analysis
Frequently Asked Questions
What rate limiting bypass techniques should I test?
Test: distributing requests across IPs, different API endpoints for same function, HTTP header manipulation (X-Forwarded-For), varying User-Agent, authenticated vs unauthenticated limits, race conditions on limit checking, and GraphQL batching to send multiple operations.
What makes rate limiting effective?
Effective rate limiting: limits per user/API key (not just IP), consistent across equivalent endpoints, includes all sensitive operations (login, password reset, data export), resists parallelization, uses sliding windows, and fails closed when limits are exceeded.
How do I test rate limiting without disrupting production?
Safe testing: use dedicated test environments, coordinate with operations, start with low request rates, monitor for alerts, use test accounts, implement kill switches in test scripts, and document expected vs. actual limits.
What are best practices for API rate limiting?
Best practices: implement per-user and per-IP limits, use token bucket or sliding window algorithms, apply stricter limits on sensitive operations, return informative rate limit headers (X-RateLimit-*), provide retry-after guidance, and monitor for abuse patterns.
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