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Description
Defensics Fuzz Testing is a robust and flexible automated black box fuzzer that helps organizations efficiently identify and address vulnerabilities in their software. This generational fuzzer employs a smart, focused methodology for negative testing, allowing users to create custom test cases through advanced file and protocol templates. Additionally, the software development kit (SDK) empowers proficient users to leverage the Defensics framework to craft their own unique test scenarios. Being a black box fuzzer means that Defensics operates without the need for source code, which adds to its accessibility. By utilizing Defensics, organizations can enhance the security of their cyber supply chain, ensuring that their software and devices are interoperable, resilient, high-quality, and secure prior to deployment in IT or laboratory settings. This versatile tool seamlessly integrates into various development workflows, including both traditional Software Development Life Cycle (SDL) and Continuous Integration (CI) environments. Furthermore, its API and data export functions facilitate smooth integration with other technologies, establishing it as a truly plug-and-play solution for fuzz testing. As a result, Defensics not only enhances security but also streamlines the overall software development process.
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
FreeBSD
Fuchsia Service Maintenance Software
NetBSD
OpenBSD
otto-js
Integrations
FreeBSD
Fuchsia Service Maintenance Software
NetBSD
OpenBSD
otto-js
Pricing Details
No price information available.
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
Black Duck
Founded
2002
Country
United States
Website
www.blackduck.com/fuzz-testing.html
Vendor Details
Company Name
Country
United States
Website
github.com/google/syzkaller