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A comprehensive guide to fuzz testing

Once you get to know more about fuzz testing, it’s easy to see why it’s become as popular as it is now.

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Security testing is one of the most vital steps to ensuring that your software is ready for its official release, whether for business purposes or commercial use. It allows you to detect any vulnerabilities your software may have and develop a countermeasure for them if a hacker takes advantage of such a flaw.

If you’re interested in security testing, you can learn the facts here now, but one thing you must know is that there all sorts of ways to conduct security testing, such as risk assessment, penetration testing, and vulnerability scanning. And if you’re already slightly familiar with security testing, you’ve probably heard of the term ‘fuzz testing.’

Fuzz testing is a relatively common testing technique in the industry nowadays, especially since corporate giants like Microsoft and Google have been using it for over a decade. But what’s surprising is that despite being a standard technique, not many people know about it. Having said that, this guide aims to explain what fuzz testing is, starting with its definition.

What Is Fuzz Testing? 

Fuzz testing, or what others call ‘fuzzing,’ involves entering invalid or random data into a program to detect any vulnerabilities that may lead to exploitable errors. This input can be in the form of a file or a direct input from the user. So, for example, if you’re building some sort of calculating program, you usually need to enter numbers or mathematical operations. But if you’re conducting fuzz testing, you’d have to enter an invalid input such as letters or even special characters.

If doing so crashes the program or causes any other kind of error, the programmer assumes that there’s a vulnerability and therefore can work on modifying the coding in hopes of fixing the problem. At first glance, you’d think that fuzz testing is the same as other techniques like vulnerability scanning or penetration testing, but there’s a reason for its popularity.

Why Do Companies Use Fuzz Testing? 

There’s no one-size-fits-all solution when it comes to security testing. Each method can detect problems that others cannot; some require lower operating costs, while others are easier to perform. Much like every security testing technique, fuzz testing is unique in its own ways. Below are a few advantages that drive companies to use fuzz testing.

  • Simplicity: You already know how fuzz testing works—it’s a matter of entering invalid input into a program. The simplicity of the process in general serves as a great advantage for individuals or organizations lacking in skills and experience in terms of security testing. 
  • Automation: Security testing might be a crucial step in software and application development, but oftentimes, there are other things to do aside from constantly testing the program. However, it’s a different story with fuzz testing since you can automate the entire process using fuzzers.

Fuzzers are tools responsible for inputting data into the program automatically if given the necessary command and conditions. The fact that fuzz testing enables business automation makes it an ideal testing technique for companies.

  • Convenient: Usually, when testing, one needs to use as many tools as possible to reduce the likelihood of bugs and maximize the program’s security. Since fuzz testing is automatable and straightforward, it’s a convenient way to enhance the software’s security. 

Fuzzing, in general, is simple and easy to implement, but it’s worth noting that there are all kinds of approaches to fuzz testing. Depending on what type you use, the difficulty and complexity of the testing process can vary. On that note, this might be a good time to talk about the different types of fuzz testing. 

Different Approaches To Fuzz Testing 

Although there are several types of fuzz testing, they’re mostly similar to one another, except that they generate input differently. Regardless, there are four approaches to fuzz testing: 

  • Dumb Fuzzing: When one wants to generate input completely randomly, they typically use a dumb fuzzer. A dumb fuzzer is a tool that produces input without prior knowledge or intelligence of the program, hence the name.

For instance, if you’re building a grammar-checking program, a dumb fuzzer may end up generating an image, which is far from what the program expects. Dumb fuzzing is the easiest approach to fuzz testing.

  • Smart Fuzzing: On the other side of the coin is smart fuzzing. Unlike dumb fuzzing, smart fuzzing generates input knowing what the program expects to receive. Moreover, a smart fuzzer won’t generate input that’ll inevitably crash the program. Instead, it will come up with input that can cause unexpected behavior.

So in the earlier example, a smart fuzzer might generate special characters but never an image or any other unsuitable input. Although smart fuzzers are more challenging to implement than dumb fuzzers, they’re more accurate most of the time.

  • Mutational Fuzzing: Mutational fuzzing involves generating input by modifying or, more specifically, ‘mutating’ an existing valid input. In our example with the calculator program, a mutational fuzzer may choose an existing valid input.

Suppose the selected input is ’10+9.’ A mutational fuzzer will try to modify this input by adding, removing, or altering a part of this input, such as increasing the value and turning it into ‘180+129′ or changing the operation to result in ’10/9.’ 

  • Generational Fuzzing: Lastly, generational fuzzing generates input from scratch, which is the opposite of mutational fuzzing that generates input from existing ones. Since there are no references, generational fuzzers are much harder to implement than mutational fuzzers, but they can lead to more data for the tester.

What makes fuzz testing a bit more interesting than other techniques is that you can combine different types to enhance the testing tool. For example, you can create a smart-mutational fuzzer or a dumb-generational fuzzer, depending on what your program needs. Perhaps the countless combinations you can perform with fuzz testing is another reason companies prefer fuzz testing over other methods. 

Wrapping Up 

Once you get to know more about fuzz testing, it’s easy to see why it’s become as popular as it is now. However, it’s also worth noting that, much like any other technique, fuzz testing has some disadvantages. Thus, it’s essential to determine whether fuzz testing can do more good than harm to your application or software. As previously said, there’s no one-size-fits-all solution for software security testing, and fuzz testing is most certainly not going to be that solution.

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