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Average Ratings 0 Ratings

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ease
features
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support

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Description

Sulley is a comprehensive fuzz testing framework and engine that incorporates various extensible components. In my view, it surpasses the functionality of most previously established fuzzing technologies, regardless of whether they are commercial or available in the public domain. The framework is designed to streamline not only the representation of data but also its transmission and instrumentation processes. As a fully automated fuzzing solution developed entirely in Python, Sulley operates without requiring human intervention. Beyond impressive capabilities in data generation, Sulley offers a range of essential features expected from a contemporary fuzzer. It meticulously monitors network activity and keeps detailed records for thorough analysis. Additionally, Sulley is equipped to instrument and evaluate the health of the target system, with the ability to revert to a stable state using various methods when necessary. It efficiently detects, tracks, and categorizes faults that arise during testing. Furthermore, Sulley has the capability to perform fuzzing in parallel, which dramatically enhances testing speed. It can also autonomously identify unique sequences of test cases that lead to faults, thereby improving the overall effectiveness of the testing process. This combination of features positions Sulley as a powerful tool for security testing and vulnerability detection.

Description

American fuzzy lop is a security-focused fuzzer that utilizes a unique form of compile-time instrumentation along with genetic algorithms to automatically generate effective test cases that can uncover new internal states within the targeted binary. This approach significantly enhances the functional coverage of the code being fuzzed. Additionally, the compact and synthesized test cases produced by the tool can serve as a valuable resource for initiating other, more demanding testing processes in the future. Unlike many other instrumented fuzzers, afl-fuzz is engineered for practicality, boasting a minimal performance overhead while employing a diverse array of effective fuzzing techniques and strategies for minimizing effort. It requires almost no setup and can effortlessly manage complicated, real-world scenarios, such as those found in common image parsing or file compression libraries. As an instrumentation-guided genetic fuzzer, it excels at generating complex file semantics applicable to a wide variety of challenging targets, making it a versatile choice for security testing. Its ability to adapt to different environments further enhances its appeal for developers seeking robust solutions.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Python Yes 
C No 
C++ No 
ClusterFuzz No 
FreeBSD No 
Go No 
Google ClusterFuzz No 
Java No 
NetBSD No 
OCaml No 
Objective-C No 
OpenBSD No 
QEMU No 
Rust No 

Integrations

Python Yes 
C Yes 
C++ Yes 
ClusterFuzz Yes 
FreeBSD Yes 
Go Yes 
Google ClusterFuzz Yes 
Java Yes 
NetBSD Yes 
OCaml Yes 
Objective-C Yes 
OpenBSD Yes 
QEMU Yes 
Rust 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 Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
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

OpenRCE

Website

github.com/OpenRCE/sulley

Vendor Details

Company Name

Google

Country

United States

Website

github.com/google/AFL

Product Features

Product Features

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