Microservices Security Testing: Risks, Types, and Checks

Mysterious microservices

Applications used to ship as a single tier. One deployable unit held the user interface, the business logic, and the data access. Teams later split that unit into smaller pieces, each responsible for one function, to make an app easier to change and to contain a failure.

The microservices architecture is a collection of small units (also addressed as containers) that together represent a finished application or solve a specific global task. Each microservice in the app is responsible for some specific functionality. The main advantage is that they can be independently deployed and tested, which brings more efficiency to the whole process of development as there is less downtime. Whereas with monoliths, it is almost impossible to do as it is a single-piece software.

Microservices can be located on different servers and operating systems and can be written in different programming languages. Many software development companies prefer to use Golang as it is suitable for microservices development. It's a highly flexible language that works quickly and significantly cuts the time spent on compiling and testing new code.

Key Takeaway: A microservices architecture splits an application into small units that each handle one function and can be deployed and tested independently, often on different servers and in different programming languages.

Are they actually safer?

They say microservices architecture is better security-wise as the functions can be tested separately. However, this technology might be a drawback as it is. Let us explain. Each microservice has a separate API, they are easily adjusted and reconfigured not bothering the whole app. It will be running despite one or two services being down at the moment. It is undoubtedly good. What's worse is that each microservice also has a number of APIs and ports thus making an app prone to intrusions. Hackers can break one API and have a path inside the app. This is why it is crucial to perform security testing thoroughly and with all the services in mind. Thus, the isolated structure makes it easier to manage, but they also bring specific challenges.

Where might be additional pitfalls? As microservices are usually all differently developed (using different programming languages at least), it's essential to ensure everything is running smoothly with no conflicting aspects. It makes testing tricky as the team should monitor and secure every service, which takes time and effort. Also, containers are replicable by nature, using the source code repeatedly. It means that any security issue in a microservice can spread quickly due to this standard.

The OWASP API Security Top 10 lists the API flaws that turn up most often across distributed services. Broken Object Level Authorization sits at API1, where a service takes an object ID from the caller and returns the record without checking that the caller owns it. Improper Inventory Management sits at API9 and matters most in microservices, because retired service versions and forgotten staging endpoints keep answering traffic after the team stops tracking them. Run both checks against every service rather than once against the whole application.

So, is microservices testing harder? We'll say, not more and not less than any other. With new technologies come new risks, and that is the idea to keep in mind.

Key Takeaway: Microservices are not safer by default, because every service adds more APIs and ports for an attacker to try and a flaw in replicated container source code spreads to every copy.

How to organize security testing?

General considerations about the application security testing are bound with the very core of the microservices nature. To track and eliminate every possible issue, the used tools and strategies need to consider their modularity, independence, and flexibility. One would not test a microservices architecture as a whole. There is a need to find tooling able to scan pieces of code (a.k.a. microservices) independently.

The chosen security solution has to focus on the following:

Code scanning

As noted earlier, the microservices source code is replicable. That is why it is necessary to conduct vulnerability scanning up to the single code line or a part of it to ensure everything is seamless and may be repeated further without causing trouble.

Adaptivity

Technologies are developing fast. However, it seems that hackers are developing even faster as each day brings new attacks and data breaches. Thus, the used security solutions have to be up to date to be able to protect microservices. Moreover, they need to be responsive to development needs. That is to be capable of assessments whenever required: continuous, scheduled, or on-demand.

Flexibility

As every microservice is to some extent custom, so has to be the security solution. Often it means having to perform separate software testing for each one. It should be possible to adjust security requests to correspond to the aim of a microservice. It is crucial to remember that to ensure thorough and accurate vulnerability testing, all of this is taken into account while performing tests. Microservices architecture is specific and needs to be treated accordingly.

Authorization coverage

Authorization has to be checked at two levels. The OWASP Microservices Security Cheat Sheet places coarse grained checks at the edge, usually an API gateway, and fine grained checks inside each service, and it warns that an edge gateway on its own becomes a single point of failure. The cheat sheet recommends defining policy centrally while each service evaluates that policy locally, so a service keeps enforcing rules when the central policy point is unreachable. It also covers identity propagation, where the caller identity reaches internal services as a data structure signed by a trusted issuer rather than as the original external token. Test both levels. Send a request straight to an internal service, bypassing the gateway, and confirm the service still refuses it, then replay a request carrying an unsigned identity structure and confirm it is rejected.

Key Takeaway: Security tooling for microservices has to scan each service independently, stay current with new attack techniques, and adapt to what an individual microservice does.

Types of testing

Base

The idea: to check whether the software works. It is the simplest test of all the basic functions of the application. This type of testing ensures the app works as intended and the distributed system is stable.

Unit

The idea: to check whether all components of the software work on their own. The number of unit tests is the largest among all the others for microservices. Unit testing is the most obvious type of testing for this architecture. The stack of technologies used depends on the language on which this microservice is written.

Integration

The idea: to check whether different services communicate properly.Integration testing is one of the most critical tests of the entire architecture. Typically, microservices communicate using APIs, so they need to be tested as well. Eliminating all possible interruptions or inaccuracies between services is important. With a positive test result, we can be sure that the entire architecture is designed correctly and all independent microservices function as a unit as intended.

Load

The idea: to check whether the app can handle daily loading. Basically, load testing checks how well the application performs under pressure of concurrent calls, downstream traffic, and interservice communications. The aim is to identify and eliminate glitches, outages, long response time latencies, or any other abnormal app behaviors.

Stress

The idea: to check whether an app has performance limits. Every product has its "ceiling". The goal here is to push the app to its limits and see how well it is performing and when does it crash.

Resiliency

The idea: to check whether an application is subject to failures. As a microservice uses the source code repeatedly, the possible failures may spread in a ripple effect. To prevent that from happening in production, resiliency testing takes place for checking the app for any of those issues.

Those six types confirm the system works and holds up under load. A security pass adds a different question: does a service refuse a caller it should refuse? NIST SP 800-204B sets out attribute-based access control inside a service mesh, with mutual TLS so every pair of services authenticates before traffic flows. Test the deny path directly by calling a service with an expired certificate, with no certificate, and with a valid certificate that carries no policy to reach that route, then confirm the mesh rejects each call.

Key Takeaway: Base, unit, integration, load, stress, and resiliency testing covers microservice behavior, and a mutual TLS deny path check confirms a service rejects a caller with a missing, expired, or unauthorized certificate.

How to security test AI services and MCP servers?

Treat an AI service as one more microservice and run the same per service checks against it. A model gateway, a retrieval service, or a Model Context Protocol (MCP) server sits behind an HTTP endpoint inside the same cluster as every other container, so it inherits the API problems described above. Two failure modes sit outside the six test types.

The OWASP Top 10 for LLM Applications 2025 lists Prompt Injection at LLM01 and Excessive Agency at LLM06. Prompt injection is a service to service problem here, because the text that reaches a model often arrives from a queue, a database row, or a retrieval index rather than from a person typing. Excessive agency is a permissions problem, because a model backed service usually holds credentials for the services it calls. Test it by revoking one downstream permission and confirming the AI service fails closed instead of reaching for a broader token.

MCP servers give you a written rule to test against. The MCP authorization specification, revision 2026-07-28, makes an MCP server an OAuth 2.1 resource server, requires it to validate that an access token was issued specifically for it as the intended audience, and forbids it from accepting or transiting any other token. Invalid or expired tokens must return HTTP 401, and a request whose token carries insufficient scope should return 403 with a WWW-Authenticate header naming the scopes the operation needs. That turns into three concrete requests: a token minted for a different internal service, an expired token, and a valid token whose scope does not cover the requested tool. Each one must be rejected, and the server must call upstream APIs with its own separate token.

Key Takeaway: An AI service or MCP server is security tested as one more microservice, with added checks that an MCP server rejects tokens that are expired, out of scope, or issued for a different service.

Is microservices testing all that special?

Yes, it is, if you want to have a quality end product for your users. It is crucial to test the microservices architecture according to its features to enjoy all the benefits of its modular structure.