What Are the Differences Between Different Open Source Fuzzing Tools

Learn more about the different fuzzing tools, their purpose, advantages and disadvantages, and differences between these tools.

Omkar Hiremath
3 min read

When developing applications, developers’ first priority is typically to make sure that the application is functioning as expected. So they primarily focus on handling expected inputs. In order to make the application robust, they also add mechanisms to handle invalid and unexpected inputs. However, sometimes there is not enough focus on the latter to cover all the cases. One of the ways attackers find points of interest to further check for vulnerabilities is by identifying the parts of the application that poorly handle malformed inputs. Therefore, you have to rigorously test your application and fix any issues. A popular method of automatically sending malformed inputs to identify flaws in the application is called Fuzzing.  In this article, we will understand what fuzzing tools are, how they work, and their purpose. Next, we will learn the differences in open-source fuzzing tools. Finally, we’ll conclude the article with the advantages and disadvantages of fuzzing tools.

What is a fuzzing tool and what is its purpose?

Fuzzing, also known as fuzz testing is a method of software testing in which a tool sends malformed data to the application to find implementation bugs. Fuzzing is an iterative process based on an initial template/payload. This is what makes fuzzing different and more relevant with each iteration than just throwing payloads at the wall. However, there are some fuzzing techniques that send random inputs. A fuzzing tool (fuzzer) is a program that automates the process of sending malformed data to the application in an attempt to cause errors. These errors indicate that there might be a bug in the code.

During the development phase, there might not have been enough focus on handling malformed inputs. Even if the developers implemented safe handling of data, it’s hard to tell that they would have thought about all the cases. This is where fuzzing comes in.

The purpose of fuzzing is to identify bugs in the application by analyzing how the application responds to malformed data. Fuzzing adds another point of view to classical software testing techniques (code review, debugging) because of its non-human approach. You should not consider fuzzing as a replacement for other testing techniques but as an addition to these techniques because different methods follow different approaches to finding bugs.

Types of fuzzing

Based on how fuzzers generate inputs, fuzzing can be categorized into 3 major types:

1. Random fuzzing

In this type of fuzzing, inputs are randomly generated with no bounds. Depending on the data, sometimes, the application might not even accept the input, or the input might not even be valid. For example, if you fuzz a JSON object to the point where it is not a JSON object, it will not work

2. Guided or behavioral fuzzing

In this type of fuzzing, the fuzzer sends an input, understands how the application responds, and then generates subsequent inputs based on the response. Here the fuzzer learns more and more about the application based on the behavior of the application and builds the context. Hence, making it more targeted than random fuzzers.

3. Template-based fuzzing

In this type of fuzzing, the fuzzer generates inputs based on a manually generated template. Individuals who have an idea about the application generate templates so the inputs are not random. The fuzzer uses this template as a reference to generate inputs.

Fuzzing is not just used to simulate user inputs, it can also be used to test programmable interfaces, such as REST APIs and network components.

Now, let’s try to understand how you can improve security with the help of fuzzing tools.

How to improve security with fuzzing

Unlike vulnerability scanners that look for known security weaknesses, fuzzers can help you find weaknesses that are unknown.

Adding this to other testing techniques increases the outcome of security testing. You can find several commercial and open-source fuzzers on the internet, each with its own pros and cons. To help you understand which open-source fuzzing tool is best for you, let us go through the differences in open-source fuzzing tools.

Differences in open-source fuzzing tools

Software fuzzing

Software fuzzing tools focus on fuzzing various types of software, including desktop and mobile and web applications. Software fuzzing tools can find a wide range of bugs such as crashes, memory leaks, input validation errors, buffer overflows, and more.

Examples of software fuzzing tools:

  • Zzuf: A general-purpose fuzzing tool that works by intercepting file operations and changing random bits in the program's input. It is easy to integrate zzuf in your pipeline and reproduce bugs.
  • AFL: AFL is a popular software fuzzing tool that uses the guided fuzzing approach. It consists of an instrumentation suite that prepares the software for fuzzing and the fuzzer itself that sends input and monitors the application’s behavior.

Cloud fuzzing

Fuzzing is not typically  applicable to cloud environments except for specific scenarios such as bucket and instance discovery. The below tools help you setup software fuzzers in cloud environments.

Examples of cloud fuzzing tools

  • Cloud_enum: Multi-cloud OSINT tool. Enumerate public resources in AWS, Azure, and Google Cloud.

API fuzzing

API fuzzing is used to test the security and robustness of application programming interfaces (APIs). It can find bugs such as input validation errors, unexpected responses, and authentication weaknesses

Examples of API fuzzing tools

  • Mayhem for API: It is a fuzzing engine that is known for its thorough test coverage. This tool was designed keeping ease of use in mind. All you need to do is upload the API specification and provide a link to the target application.
  • ffuf: ffuf is a simple and one of the fastest API fuzzing tool. To define test cases in ffuf, all you have to do is use the keyword FUZZ anywhere in the URL, headers, or request body.

URL fuzzing

This type of fuzzing involves sending a large number of HTTP requests to a web application with various URL paths and parameters. It can help identify bugs such as misconfigured web servers, and unauthorized access to restricted pages and path traversal issues

Examples of URL fuzzing tools

  • dirb: dirb uses dictionary-based fuzzing with a set of preconfigured wordlists and analyzes the responses to search for hidden directories and paths. It also allows you to use custom wordlists if you have anything specific to look for, like framework resources, sensitive login pages, admin panels, and more.
  • Gobuster: This is one of the most popular tools that fuzzes URIs and subdomains. In addition to that, it can also be used to brute-force hostnames, Amazon S3, and Google Cloud buckets.
  • Sublist3r: It is a python-based sub-domain enumerator.

Protocol fuzzing

This type of fuzzing involves testing the robustness of various network protocols, including TCP/IP, DNS, and SSL/TLS. It can be used to find bugs and vulnerabilities in communication protocols, including network traffic analysis and identification of vulnerabilities in network devices and services.

Examples of protocol fuzzing tools

  • Sulley: It is a protocol fuzzing tool that is designed to be extensible and can be used to test a range of different network protocols. It simplifies data representation, transmission, and instrumentation. The developers have named this tool after a character from the movie Monsters Inc. because the tool is so “fuzzy”.
  • Peach Fuzzer: It is a cross-platform fuzzer capable of fault detection, data collection, and automation of the fuzzing environment. Peach fuzzer’s highlight its extensibility in mutation algorithms, data types, I/O adapters, monitoring modules, etc.
  • WsProxy: WsProxy is a tool built by a SoftwareSecured pentester for the sole purpose of testing the websocket protocol. It is capable of fuzzing websockets on the application layer as well as the protocol layer.

File format fuzzing

This type of fuzzing involves testing the robustness of file parsers and other software components that deal with file formats. It can be used to find vulnerabilities such as buffer overflows and other issues related to the parsing and handling of files.

Examples of file format fuzzing tools

There are not a lot of open-source file format fuzzing tools. Tools like Peach Fuzzer and AFL also provide file format fuzzing. Apart from that, here are some other tools:

  • FileFuzz: It is a graphical Windows-based tool. It automatically creates abnormal file formats, launches applications handling these files, and detects exceptions caused by fuzzed file formats.
  • BFF: CERT BFF - Basic Fuzzing Framework (BFF) is fuzzing tool that can be used to test a range of different binary file formats, including executables, libraries, and document files. It requires minimal initial configuration and supervision and is backed by machine learning.

The breadth of testing that can be done using fuzzing is impressive. With the wide range of target platforms and tools, fuzzing can really enhance testing.

Advantages and disadvantages of fuzzing tools


  • Fuzzing tools can cover a large portion of the input space in a relatively short amount of time. It requires less investment and resources to start with especially for simple applications. However, the time and output of fuzzing vary based on the setup.
  • Fuzzing tools can automate part of the testing process, freeing up testers to focus manual testing on other areas of the application. You can also integrate fuzzing tools in your pipeline or with your test suites making it easy to adapt.
  • Fuzzing tools can generate a wide range of test data from completely random inputs to template-based and guided fuzzing, to test for various types of scenarios.
  • Fuzzing tools help identify zero-day exploits. You will not just be able to identify points of weakness but also what kind of inputs can be used to exploit them.  


  • Fuzzing tools by themselves do not guarantee comprehensive security testing. You will still need to exercise other testing techniques.  
  • Fuzzing tools are generally only able to hint that there might be a vulnerability but can not confirm that the vulnerability exists.
  • Fuzzing tools can generate a large number of false positives and negatives. Therefore,
  • Fuzzing tools are not able to provide context around the application and how it works. This can make it difficult to understand the significance of any vulnerabilities found or how they could be exploited in the real world.


Fuzzing is a robust method for testing application security with relatively little overhead. Depending on your use case, you can use various types of fuzzing listed above to conduct security testing across your application. In this article, we covered what fuzzing tools are, their purpose, and the different categories of fuzzing.

Fuzzing has become increasingly popular in recent years due to its ability to detect a wide range of bugs and vulnerabilities that traditional testing methods may miss. Fuzzing tools use various techniques to generate inputs that can perform tests in a comprehensive and efficient manner. By incorporating fuzzing into testing strategies, you can enhance the outcome of your testing process. There are various purpose-built tools that are only good at doing exactly what they do. However, it is important to note that it is always recommended to use these tools along with other security testing practices and not as a replacement.

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Omkar Hiremath

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