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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
Syzkaller functions as an unsupervised, coverage-guided fuzzer aimed at exploring vulnerabilities within kernel environments, offering support for various operating systems such as FreeBSD, Fuchsia, gVisor, Linux, NetBSD, OpenBSD, and Windows. Originally designed with a focus on fuzzing the Linux kernel, its capabilities have been expanded to encompass additional operating systems over time. When a kernel crash is identified within one of the virtual machines, syzkaller promptly initiates the reproduction of that crash. By default, it operates using four virtual machines for this reproduction process and subsequently works to minimize the program responsible for the crash. This reproduction phase can temporarily halt fuzzing activities, as all VMs may be occupied with reproducing the identified issues. The duration for reproducing a single crash can vary significantly, ranging from mere minutes to potentially an hour, depending on the complexity and reproducibility of the crash event. This ability to minimize and analyze crashes enhances the overall effectiveness of the fuzzing process, allowing for better identification of vulnerabilities in the kernel.
API Access
Has API
API Access
Has API
Integrations
Docker
FreeBSD
Fuchsia Service Maintenance Software
NetBSD
OpenBSD
Python
Integrations
Docker
FreeBSD
Fuchsia Service Maintenance Software
NetBSD
OpenBSD
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
Country
United States
Website
github.com/google/syzkaller