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Description
Radamsa serves as a robust test case generator specifically designed for robustness testing and fuzzing, aimed at evaluating how resilient a program is against malformed and potentially harmful inputs. By analyzing sample files containing valid data, it produces a variety of uniquely altered outputs that challenge the software's stability. One of the standout features of Radamsa is its proven track record in identifying numerous bugs in significant programs, alongside its straightforward scriptability and ease of deployment. Fuzzing, a key technique in uncovering unexpected program behaviors, involves exposing the software to a wide range of input types to observe the resultant actions. This process is divided into two main components: sourcing the diverse inputs and analyzing the outcomes, with Radamsa effectively addressing the first component, while a brief shell script generally handles the latter. Testers often possess a general understanding of potential failures and aim to validate whether those concerns are warranted through this method. Ultimately, Radamsa not only simplifies the testing process but also enhances the reliability of software applications by revealing hidden vulnerabilities.
Description
AFL-Unicorn provides the capability to fuzz any binary that can be emulated using the Unicorn Engine, allowing you to target specific code segments for testing. If you can emulate the desired code with the Unicorn Engine, you can effectively use AFL-Unicorn for fuzzing purposes. The Unicorn Mode incorporates block-edge instrumentation similar to what AFL's QEMU mode employs, enabling AFL to gather block coverage information from the emulated code snippets to drive its input generation process. The key to this functionality lies in the careful setup of a Unicorn-based test harness, which is responsible for loading the target code, initializing the state, and incorporating data mutated by AFL from its disk storage. After establishing these parameters, the test harness emulates the binary code of the target, and upon encountering a crash or error, triggers a signal to indicate the issue. While this framework has primarily been tested on Ubuntu 16.04 LTS, it is designed to be compatible with any operating system that can run both AFL and Unicorn without issues. With this setup, developers can enhance their fuzzing efforts and improve their binary analysis workflows significantly.
API Access
Has API
API Access
Has API
Integrations
FreeBSD
Git
Make
OpenBSD
Pricing Details
Free
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Aki Helin
Website
gitlab.com/akihe/radamsa
Vendor Details
Company Name
Battelle
Website
github.com/Battelle/afl-unicorn