This is the security leak that your tests are blind for

Ask a random CIO or IT manager what the biggest security risks are, and you'll quickly hear terms such as phishing, ransomware, or misconfigurations in the cloud. But almost no one mentions the risk of... slow software.

And yet that's exactly where things often go wrong.

Security tests are usually carried out properly. There are functional tests, there are penetration tests, and here and there you also find performance tests. But they are almost never carried out in conjunction with each other. And that is precisely the problem. It means that we don't know how secure software still is when its performance is under pressure.

• What happens to your login processes when thousands of users log in simultaneously and response times spike?

• How does an API behave when latency increases and timeouts occur?

• What if load balancing suddenly causes traffic to go through an untested path?

Most security tests are conducted in a “clean” laboratory environment, often with a limited number of users and a healthy response time. As soon as the software is scaled up to the real world—with peak loads, slow queries, and faltering user experience—the gaps appear.

And that poses serious risks, such as:

• Users who log in via alternative routes.

• Session tokens that unintentionally remain valid for longer.

• Timeouts that lead to incomplete validation.

• Or simply: developers who build in “temporary” shortcuts to keep slow software usable.

The result: a system that looks secure on paper, but in practice offers openings that malicious parties can easily exploit.

In this blog, I will show you how performance issues undermine security—and what you can do about it.

The door that's wide open to data breaches

Software behaves differently at scale than it does in the test environment. Always. Yet most security tests are performed with... one user. Maybe two. And very occasionally with a handful.

But the real world doesn't work with one or a handful of users. Thousands of people log in to common systems at the same time. Multiple APIs run queries on the same database simultaneously. This creates queues, timeouts, and race conditions. And that's exactly where the holes in your security creep in.

What can happen as a result?

• Session leaks: data from user A accidentally ends up in user B's session.

• Lock timeouts: simultaneous transactions block each other, after which error handling is “temporarily” bypassed—with lasting consequences.

• API pollution: endpoints that appeared to be perfectly isolated turn out to have dependencies in practice.

• Timing attacks: small delays give hackers just enough information to bypass validations.

The tricky thing is that these kinds of problems only pop up when software is under pressure. Everything looks fine in your penetration test report or QA file. But as soon as the load peaks—due to scale, growth, or unexpected peak loads—you open the door to data leaks and abuse.

The reality is that software that appears secure in a laboratory situation can be dangerous once it is actually used. It's like testing a bridge with a single car and then expecting it to handle trucks and traffic jams with ease.

If you don't test for scale, you're not really testing security at all.

Attackers love containers

Containers have taken the world by storm. They are flexible, scalable, and seem to be the perfect solution for modern applications. Scaling from ten to a hundred instances now only takes a few lines of configuration. But... with that flexibility comes a risk that many companies underestimate: security.

Now you might think, “You see a bear behind every tree.”

I say: we have to find all the bears if you take your security seriously.

Because how stable – and therefore secure – does your application remain when a hundred containers have to work together at the same time? The answer: much less stable than you might think.

Take sessions, for example. When a user is sent to another container by a load balancer, their entire session – including all data and permissions – must be transferred. But where is that session actually managed? How reliable is that transfer? And what happens if the same user opens multiple sessions that end up on different containers?

There's something else to consider: locking. In an ideal world, containers communicate neatly with each other and prevent transactions from interfering with each other. In practice, this often goes wrong. The result: race conditions, incomplete validations, and, in the worst case, data leaks.

And the more containers you add, the greater the chance that something will break. One container that handles a session incorrectly is already a problem. A hundred containers that all have the potential for that problem is a nightmare. Especially when this scenario has never been tested.

Containers are brilliant for rapid growth. But if your security tests don't grow with that scale, you create exactly the kind of holes that attackers are waiting for.

The conclusion is simple: if you scale containers without stress testing, you scale your risks just as fast.

How performance errors expose your security

Everyone knows the situation: an application crashes, the user gets an error message on the screen and tries again. Frustrating for the user. A gold mine for an attacker.

Because what does that error message actually say?

In functional tests, error messages are often checked thoroughly. Security tests usually do the same. But when it comes to performance, people only look at the number of timeouts or failed requests. They don't look at the content of those error messages.

And that's where it goes wrong.

Performance errors often reveal more than you would like. A delayed query that no longer responds may simply display an internal exception. A timeout may reveal which database user the query was running under. Or which module and function crashed. Sometimes even with parameters included. All intended for developers, so they can quickly resolve the issue.

But for malicious parties, these are roadmaps. They learn about your internal architecture, which components are weak, which accounts have access, and how the data flow works. This is exactly the information needed to plan the next attack.

The irony is that these kinds of errors don't occur when a single user is quietly clicking through a test environment. They only occur under real load. When hundreds of users log in at the same time. When an API overflows. When the system slows down and starts to falter.

In other words, as long as you only test in “happy flow” situations, you keep these leaks completely out of sight. Until a hacker finds them for you.

Conclusion: poor performance is not just a user problem. It is a direct invitation to intruders.

Now is the time for action.

On paper, almost every application is secure. In the lab, too. But with hundreds of users, peak loads, and slow response times, gaps appear.

So the question is not: is my software secure?

The question is: how insecure is my software at scale?

If you want to know this, if you want to know how insecure your software is at scale, make an appointment. The first appointment is always free, but never for nothing. Together, we will look at where the hidden risks lie in your organization and how you can solve them before they cost you (and your data) dearly.

👉 Book your consultation now. Because safety at scale is not a luxury, but a prerequisite.

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