Average Ratings 0 Ratings
Average Ratings 0 Ratings
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.
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
No
API Access
Has API
No
Integrations
FreeBSD
Yes
NetBSD
Yes
OpenBSD
Yes
C
Yes
C++
Yes
ClusterFuzz
Yes
Fuchsia Service Maintenance Software
No
Go
Yes
Google ClusterFuzz
Yes
Java
Yes
Integrations
FreeBSD
Yes
NetBSD
Yes
OpenBSD
Yes
C
No
C++
No
ClusterFuzz
No
Fuchsia Service Maintenance Software
Yes
Go
No
Google ClusterFuzz
No
Java
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
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
Country
United States
Website
github.com/google/AFL
Vendor Details
Company Name
Country
United States
Website
github.com/google/syzkaller