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Average Ratings 0 Ratings
Description
Atheris is a Python fuzzing engine guided by coverage, designed to test both Python code and native extensions developed for CPython. It is built on the foundation of libFuzzer, providing an effective method for identifying additional bugs when fuzzing native code. Atheris is compatible with Linux (both 32- and 64-bit) and Mac OS X, supporting Python versions ranging from 3.6 to 3.10. Featuring an integrated libFuzzer, it is well-suited for fuzzing Python applications, but when targeting native extensions, users may need to compile from source to ensure compatibility between the libFuzzer version in Atheris and their Clang installation. Since Atheris depends on libFuzzer, which is a component of Clang, users of Apple Clang will need to install a different version of LLVM, as the default does not include libFuzzer. The implementation of Atheris as a coverage-guided, mutation-based fuzzer (LibFuzzer) simplifies the setup process by eliminating the need for input grammar definition. However, this approach can complicate the generation of inputs for code that processes intricate data structures. Consequently, while Atheris offers ease of use in many scenarios, it may face challenges when dealing with more complex parsing requirements.
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.
API Access
Has API
Yes
API Access
Has API
No
Integrations
FreeBSD
No
Git
No
Google OSS-Fuzz
Yes
LibFuzzer
Yes
Make
No
OpenBSD
No
Python
Yes
Integrations
FreeBSD
Yes
Git
Yes
Google OSS-Fuzz
No
LibFuzzer
No
Make
Yes
OpenBSD
Yes
Python
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Website
github.com/google/atheris
Vendor Details
Company Name
Aki Helin
Website
gitlab.com/akihe/radamsa