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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

Awesome Fuzzing serves as a comprehensive compilation of resources for those interested in the field of fuzzing, encompassing an array of materials such as books, both free and paid courses, videos, tools, tutorials, and vulnerable applications ideal for hands-on practice to enhance one's understanding of fuzzing and the early stages of exploit development, including root cause analysis. It features instructional videos focused on fuzzing methodologies, essential tools, and recommended practices, alongside conference presentations, tutorials, and blogs dedicated to the subject. Additionally, it includes software tools that facilitate fuzzing of applications, particularly those utilizing network protocols like HTTP, SSH, and SMTP. Users are encouraged to search for and select exploits linked to downloadable applications, where they can then recreate the exploits with their preferred fuzzer. The resource also encompasses a range of tests tailored for fuzzing engines, highlighting various well-known vulnerabilities and providing a corpus of diverse file formats to enable fuzzing across multiple targets found in the existing fuzzing literature. Ultimately, this collection aims to empower learners with the necessary knowledge and skills to effectively engage with fuzzing techniques and develop their expertise in security testing.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google OSS-Fuzz Yes 
LibFuzzer Yes 
Python Yes 

Integrations

Google OSS-Fuzz No 
LibFuzzer No 
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 Yes 
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

secfigo

Website

github.com/secfigo/Awesome-Fuzzing

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Product Features

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