Customization

Extend and Customize

FuzzLabs’ modular design enables unparalleled flexibility to supports a wide variety of use cases. Every aspect of FuzzLabs can be easily extended and fine-tuned to any environment.

Unparalleled Flexibility and Customization

The module design of FuzzLabs’ Attack Simulation Engine (ASE) enables unparalleled flexibility to supports a wide variety of use cases. Every aspect of FuzzLabs can be easily extended and fine-tuned to any environment, ultimately lowering the barrier of entry and helping adoption across the organization.

If you ever felt the need to “create your own,” FuzzLabs was made for you!

Mutation Engine

The proprietary mutation engine of FuzzLabs is capable of generating test cases to cover even the most complicated protocols and data structures. A wide variety of supported field types and applicable layered transformations make it trivial to deal with encodings, encrypting, hash and checksum calculations, and encrypted blocks. What is even better, the SDK enables users to create custom field types and transformations.

Test Delivery

FuzzLabs’ Attack Simulation Engine can deliver test cases over the network, via the command line or, by generating mutated files. The SDK allows for easy implementation of additional delivery methods, such as Bluetooth, CAN, and serial line.

Target Monitoring

FuzzLabs is capable of detecting unintended behavior triggered by the test cases in several different ways. FuzzLabs can monitor the process state using a remote GDB connection or look for indicators in logs files, all of these at the same time. The SDK enables straightforwardly extending the monitoring capabilities to monitor resource usage, device reboot, or any other aspect of the target.

Test Case Generation

FuzzLabs is a hybrid fuzzer capable of utilizing generation-based and mutation-based fuzzing techniques, even in combination. The hybrid test generation approach allows improving your fuzz testing program’s maturity over time.

Generation-Based

Generate test cases based on templates describing structured data. Each field within the structured data is mutated using a set of dedicated algorithms. This approach’s main benefit is accuracy, the ability to test complex data structures, and shorter test run time.

Mutation-Based

Generate test cases by mutating “unknown” data structures. This approach’s main benefit is that there is no need to model structured data; thus, you can start fuzzing quickly.

Hybrid

The hybrid test generation approach allows improving your fuzz testing program’s maturity over time.
The mutation-based method allows running tests straight away. Later on, parts of the mutated data can be parsed into fields, gradually handing over the test case generation to the generation-based algorithms.

Visual Protocol Modeler

The Visual Protocol Modeler enables users to describe complex data structures without writing a single line of code. The intuitive, drag-and-drop interface drastically simplifies and speeds up the templating process and reduces errors.