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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

Peach is an advanced SmartFuzzer that excels in both generation and mutation-based fuzzing techniques. It necessitates the creation of Peach Pit files, which outline the data's structure, type information, and interrelations for effective fuzzing. In addition, Peach provides customizable configurations for a fuzzing session, such as selecting a data transport (publisher) and logging interface. Since its inception in 2004, Peach has undergone continuous development and is currently in its third major iteration. Fuzzing remains one of the quickest methods to uncover security vulnerabilities and identify bugs in software. By utilizing Peach for hardware fuzzing, students will gain insights into the essential principles of device fuzzing. Designed to address any data consumer, Peach can be applied to servers as well as embedded devices. A wide array of users, including researchers, companies, and government agencies, leverage Peach to detect hardware vulnerabilities. This course will specifically concentrate on employing Peach to target embedded devices while also gathering valuable information in case of a device crash, thus enhancing the understanding of fuzzing techniques in practical scenarios.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Python Yes 
.NET No 
GitLab No 
Google OSS-Fuzz Yes 
LibFuzzer Yes 
Visual Studio No 
XML No 

Integrations

Python Yes 
.NET Yes 
GitLab Yes 
Google OSS-Fuzz No 
LibFuzzer No 
Visual Studio Yes 
XML Yes 

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

Google

Website

github.com/google/atheris

Vendor Details

Company Name

Peach Tech

Founded

2004

Country

United States

Website

peachtech.gitlab.io/peach-fuzzer-community/

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Product Features

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