Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Wfuzz offers a powerful platform for automating the assessment of web application security, assisting users in identifying and exploiting potential vulnerabilities to enhance the safety of their web applications. Additionally, it can be executed using the official Docker image for convenience. The core functionality of Wfuzz is based on the straightforward principle of substituting any occurrence of the fuzz keyword with a specified payload, which serves as a source of data. This fundamental mechanism enables users to inject various inputs into any field within an HTTP request, facilitating intricate attacks on diverse components of web applications, including parameters, authentication mechanisms, forms, directories and files, headers, and more. Wfuzz's scanning capabilities for web application vulnerabilities are further enhanced by its plugin support, which allows for a wide range of functionalities. As a completely modular framework, Wfuzz invites even novice Python developers to contribute easily, as creating plugins is a straightforward process that requires only a few minutes to get started. By harnessing the power of Wfuzz, security professionals can significantly improve their web application defenses.

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

Screenshots View All

Screenshots View All

Integrations

Docker
Python

Integrations

Docker
Python

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

Wfuzz

Website

wfuzz.readthedocs.io

Vendor Details

Company Name

Battelle

Website

github.com/Battelle/afl-unicorn

Product Features

Product Features

Alternatives

Alternatives

API Fuzzer Reviews

API Fuzzer

Fuzzapi
UMT Unicorn 10 Reviews

UMT Unicorn 10

Usha Martin Technologies