I’ve spent the last 25 years building—and breaking—a wide variety of APIs, and one lesson has stood out more than any other: security is never “done.” In this deep dive, I’ll walk you through the most common mistakes I’ve seen (even from seasoned engineers), share real-world consequences, and offer concrete, step-by-step advice for both REST and GraphQL APIs. Strap in—this is a journey through decades of hard-earned lessons.
Why API Security Matters
APIs are the backbone of modern applications—powering mobile apps, single-page web apps, IoT devices, and even partner integrations. Yet they also represent one of the most frequent vectors for data breaches and service disruptions. In 2024 alone, over 40% of reported data leaks involved misconfigured or insecure APIs, according to industry surveys.¹ As I often remind my teams, “An insecure API is like an unlocked front door—you may not notice right away, but someone will stroll in eventually.”
“APIs are the new attack surface. If you leave a crack, adversaries will pry it open.”
— Tech Security Weekly, 2024
Securing your APIs isn’t a one-off task; it’s an ongoing practice woven into your design, development, and deployment cycles.
Common Mistakes Even Experienced Developers Make
In my career, I’ve audited hundreds of APIs. Here are the top blunders I keep encountering:
- Overly Permissive CORS Policies
Granting broad cross-origin access without validating origins. - Insufficient Authentication & Authorization
Assuming user identity is always trustworthy, or over-relying on client-side controls. - Lack of Rate Limiting
Leaving endpoints open to brute-force or denial-of-service attacks. - Exposing Internal Error Details
Returning full stack traces in JSON responses, which reveal your technology stack. - Inadequate Input Validation
Allowing SQL- and NoSQL-injection, or failing to sanitize GraphQL queries. - Ignoring TLS Best Practices
Using deprecated ciphers or allowing weak SSL versions. - Deploying with Debug Flags Enabled
Accidentally shipping code with DEBUG=true, exposing sensitive data in logs.
Real-World Examples and Remedies
Below is a snapshot of mistakes I’ve encountered, their consequences, and the fixes I recommended:
| Mistake | Consequence | My Recommendation |
| Open Access-Control-Allow-Origin: * | Attackers host malicious front-ends that hijack tokens | Restrict CORS to known domains |
| Missing JWT revocation | Users retain access after password reset or compromise | Implement token blacklists or short TTLs |
| Unthrottled login endpoint | Credential-stuffing and account lockouts | Enforce rate limits and account lockouts |
| Verbose error messages | Leakage of schema, libraries, and framework versions | Return generic errors; log details server-side |
| GraphQL introspection in production | Exposes full schema, enabling targeted attacks | Disable introspection or whitelist fields |
| Allowing eval() in input handling | Remote code execution via malicious payloads | Use safe parsers; never evaluate raw input |
| Hard-coded API keys in repositories | Complete account takeover if code is leaked | Use vaults or environment variables only |
Best Practices for REST APIs
When designing or reviewing a REST API, I always follow these steps:
- Enforce Principle of Least Privilege
Ensure every endpoint checks both authentication (who you are) and authorization (what you can do). I once saw a payment API that let any authenticated user trigger refunds for any order ID—disaster waiting to happen. - Validate Inputs Rigorously
Use schema validation libraries (e.g., Joi, JSON Schema) to reject unexpected or malicious payloads. I recommend centralizing validation logic so that every microservice enforces the same rules. - Implement Rate Limiting & Throttling
Protect critical endpoints (login, password reset, data exports) with IP-based or token-based throttles. In one incident, a client lost service for hours because a competitor launched a brute-force campaign against their unsecured billing API. - Sanitize All Outputs
Never reflect raw user input back to clients without encoding or escaping. This prevents cross-site scripting (XSS) in API-driven UIs. - Adopt Secure Defaults
Ship frameworks and libraries with safe default settings. Audit your dependencies quarterly and subscribe to vulnerability alerts.
Securing GraphQL Endpoints
GraphQL’s flexibility brings unique risks. Here’s how I harden my GraphQL servers:
- Query Depth Limiting
Prevent deeply nested queries that exhaust server resources. I usually cap depth at 5 levels for public endpoints. - Complexity Analysis
Assign cost scores to fields and reject queries surpassing a complexity threshold. For example, a single user { posts { comments } } query might count as 10 points—reject anything over 100. - Disable Introspection in Production
Avoid exposing your entire schema to untrusted clients. I keep introspection enabled in staging but turn it off behind a feature flag in production. - Field-Level Authorization
Enforce per-field access controls—just because a user can query user.email doesn’t mean they should. I integrate with my RBAC system at the resolver level. - Batch Request Protection
Block or throttle persisted query abuse by validating incoming operation IDs.
Two Lists of Critical Security Measures
Below are two focused checklists you can integrate into your sprint reviews:
Checklist A: Pre-Deployment Security Gates
- Dependency vulnerability scan passed
- Linting enforces secure code patterns
- Automated penetration tests green
- Secrets not present in codebase
- TLS certificates up-to-date and pinned
Checklist B: Live Production Monitoring
- Alert on spikes in 4xx/5xx status codes
- Monitor average response times for anomalies
- Track unusual spike in GraphQL query complexity
- Log and review all CORS rejections
- Rotate keys and tokens periodically
“You can’t secure what you don’t understand.”
— In my many years of API security audits, the first step is always a complete map of your endpoints, data flows, and trust boundaries.
Layered Defense: Putting It All Together
API security isn’t a checkbox—it’s layered defense. Here’s my recommended approach:
- Design Phase
- Threat model your API before writing code.
- Define clear trust zones and data sensitivity levels.
- Threat model your API before writing code.
- Development Phase
- Integrate static analysis tools (SAST) into your CI pipeline.
- Write unit tests for every custom security rule.
- Integrate static analysis tools (SAST) into your CI pipeline.
- Pre-Production Phase
- Run dynamic analysis (DAST) against staging APIs.
- Perform manual code reviews for critical endpoints.
- Run dynamic analysis (DAST) against staging APIs.
- Production Phase
- Enforce Web Application Firewalls (WAF) with API-aware rules.
- Continuously monitor logs and metrics for anomalies.
- Enforce Web Application Firewalls (WAF) with API-aware rules.
- Post-Incident Phase
- Conduct root-cause analysis and update playbooks.
- Share learnings across teams and update your API security guidelines.
- Conduct root-cause analysis and update playbooks.
Securing APIs is a living process. By learning from the mistakes above and embedding security into every phase—design through monitoring—you’ll stay one step ahead of attackers and sleep a little easier at night. Remember: “Security isn’t a product; it’s a process.”