Best Practices for REST API Testing

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The Challenges of REST API Testing

Securing REST APIs is a challenging task, as they are highly complex: They are difficult to reach, produce countless parameter combinations, and constantly communicate with a vast number of other systems. Looking for security vulnerabilities in REST APIs manually is like looking for a needle in a haystack. To deal with the complexity of REST APIs, many dev teams test APIs with automated methods. Below, you can find an overview of the top 6 challenges of REST API testing.

1. Securing REST API Parameter Combinations

As presented below, REST APIs consist of various different parameters such as request method, request URI and query parameter - just to name a few. These parameters can take up countless combinations that have to be tested, as specific parameter combinations can lead to erroneous program states.

2. Validating REST API Parameters

Validating REST API parameters is highly challenging. If they are not validated properly, issues such as wrong string/data types and parameter data outside the predefined value range can come up.

3. Maintaining the Data Formatting Schema

The data formatting schema specifies how REST APIs handle responses and requests. The challenge in maintaining data formatting is that whenever new parameters are added, they have to be included in the schema.

4. Testing REST API Call Sequences

Testers need to ensure that REST API calls are called in the correct order to prevent errors. In REST APIs this is especially important since they are generally multithreaded.

5. REST API Testing Set-Up

Setting up automated testing cycles is the part of REST API testing that requires the most manual effort. Especially for large projects enterprise testing platforms will help you speed up the initial set-up dramatically.

6. Error Reporting for REST APIs

Especially with black-box testing tools, error reporting for REST APIs is tricky, as the amount of tested parameter combinations is unknown. The best way to monitor and report REST API tests is with coverage-guided testing approaches, as they can provide meaningful coverage and error reports.

How to Automate Robustness Testing for REST APIs

Due to the complex structure of REST APIs, automated testing is one of the most effective ways to ensure their security and stability. But not all automated testing approaches are equally effective. The fastest way to implement software test automation would be with black-box API testing tools, such as Burp or OWASP ZAP, potentially enhanced with some additional system tests.

Although these black-box approaches are somewhat automated, they leave plenty of room for improvement, as they still require testers to have prior knowledge about the system under test in order to be effective. Black-box tests are great to test APIs from an attacker's perspective. They generate test inputs randomly, from static corpora, from OpenAPI imports, or based on heuristics. However, such inputs often fail to reach complex vulnerabilities and edge cases, since they do not take code coverage into account. For example, a black-box testing tool would take the API request from above and try out countless different parameter settings in hopes of identifying a request that breaks something.

Automated white-box testing is far more effective at finding buggy REST API requests: Since they use information about the source code, white-box approaches can automatically exclude irrelevant parameter settings from the corpus. Through information about code coverage, they can find crashing REST API requests much faster and much more accurately. White-box automation also enables better reporting by providing code-coverage visibility. The advantages of this approach are especially useful to secure vast microservice environments that are connected through APIs, and projects that are expanding in size.

Testing Before Deploying vs After Deploying

While there are several different ways to test a REST API, one of the most helpful distinctions is to consider testing before and after deploying a service. In this case, this could mean deploying a REST API to a development environment or developer’s workstation, deploying to an internal-only test or staging environment for testing by multiple individuals and teams, or deploying to production to some or all end users. Testing before deployment usually means unit testing, and testing either the underlying business logic of a REST API as well as the API service itself. Both testing before and after deployment are critical to ensure a high quality API.

Testing before deployment is effective for testing business logic and rules of the service. Functional unit testing is an excellent approach here, since the developer has full control over the source code and can create unit test cases based on the business requirements. Finding bugs and security vulnerabilities based on unit testing before deployment greatly reduces the risk of such defects affecting end users or even other developer teams that may use the API service. In addition, testing pre-deployment has the benefit of significantly faster execution time, since network connections are confined to a single machine or mocked out completely. 

Security testing before deployment also has the benefit of lower execution time, Fuzz testing can be used to find major security vulnerabilities and defects in both the business logic layer and REST API service layer. The increased speed in testing pre-deployment increases the effectiveness of fuzzing overall. Security testing using fuzzing is an excellent way for application developers to “shift left” while using familiar test frameworks and tools.

Fuzz Testing for REST APIs

The most efficient way to implement automated white-box testing is with feedback-based fuzzing. Feedback-based fuzz testing is a form of data-driven testing, during which code instrumentation is used to measure the test progress within individual microservices and APIs. Through this instrumentation, the fuzzer collects information about test inputs, which it then uses to create further inputs that traverse even more code paths. Modern fuzzers can be customized to scan for specific bug classes and to remove blockers. Since this technology can be integrated into any build system, it enables developers to continuously test APIs for security vulnerabilities and stability issues. 

As mentioned above, fuzzing a service pre-deployment or in-process is a great approach for security testing of a REST API because of the reduced latency of local testing. This allows feedback-based fuzz testing to execute faster and find vulnerabilities efficiently. Developers can take advantage of fuzzing during development of an API to find vulnerabilities even before deploying a service to an internal test environment. 

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