Audience
Developers looking for a solution to manage their network protocol fuzzing operations
About Boofuzz
Boofuzz is a fork of and the successor to the venerable Sulley fuzzing framework. Besides numerous bug fixes, Boofuzz aims for extensibility. Like Sulley, Boofuzzincorporates all the critical elements of a fuzzer like easy and quick data generation, instrumentation and failure detection, target reset after failure, and recording of test data. Much easier install experience and support for arbitrary communications mediums. Built-in support for serial fuzzing, ethernet- and IP-layer, UDP broadcast. Better recording of test data, consistent, thorough, and clear. Test result CSV export and extensible instrumentation/failure detection. Boofuzz installs as a Python library used to build fuzzer scripts. It is strongly recommended to set up Boofuzz in a virtual environment.
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Fuzz testing or fuzzing is a software testing technique, that basically consists in finding implementation bugs using malformed/semi-malformed data injection in an automated fashion. Let’s consider an integer in a program, which stores the result of a user’s choice between 3 questions. When the user picks one, the choice will be 0, 1, or 2, which makes three practical cases. Integers are stored as a static size variable. If the default switch case hasn’t been implemented securely, the program may crash and lead to “classical” security issues. Fuzzing is the art of automatic bug finding, and its role is to find software implementation faults and identify them if possible. A fuzzer is a program that automatically injects semi-random data into a program/stack and detects bugs. The data-generation part is made of generators, and vulnerability identification relies on debugging tools. Generators usually use combinations of static fuzzing vectors.
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LibFuzzer
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Sulley
Sulley is a fuzzing engine and fuzz testing framework consisting of multiple extensible components. Sulley (IMHO) exceeds the capabilities of most previously published fuzzing technologies, commercial and public domain. The goal of the framework is to simplify not only data representation but to simplify data transmission and instrumentation. A pure-Python fully automated and unattended fuzzing framework. Sulley not only has impressive data generation but has taken this a step further and includes many other important aspects a modern fuzzer should provide. Sulley watches the network and methodically maintains records. Sulley instruments and monitors the health of the target, capable of reverting to a known good state using multiple methods. Sulley detects, tracks, and categorizes detected faults. Sulley can fuzz in parallel, significantly increasing test speed. Sulley can automatically determine what unique sequence of test cases triggers faults.
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Free Version available.
Company Information
Boofuzz
boofuzz.readthedocs.io/en/stable/
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