About
ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection.
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About
LibFuzzer is an in-process, coverage-guided, evolutionary fuzzing engine. LibFuzzer is linked with the library under test, and feeds fuzzed inputs to the library via a specific fuzzing entry point (or target function); the fuzzer then tracks which areas of the code are reached, and generates mutations on the corpus of input data in order to maximize the code coverage. The code coverage information for libFuzzer is provided by LLVM’s SanitizerCoverage instrumentation. LibFuzzer is still fully supported in that important bugs will get fixed. The first step in using libFuzzer on a library is to implement a fuzz target, a function that accepts an array of bytes and does something interesting with these bytes using the API under test. Note that this fuzz target does not depend on libFuzzer in any way so it is possible and even desirable to use it with other fuzzing engines like AFL and/or Radamsa.
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About
Peach is a SmartFuzzer that is capable of performing both generation and mutation-based fuzzing. Peach requires the creation of Peach Pit files that define the structure, type information, and relationships in the data to be fuzzed. It additionally allows for the configuration of a fuzzing run including selecting a data transport (publisher), logging interface, etc. Peach has been under active development since 2004 and is in its third major version. Fuzzing continues to be the fastest way to find security issues and test for bugs. Effective hardware fuzzing with Peach will introduce students to the fundamentals of device fuzzing. Peach was designed to fuzz any type of data consumer from servers to embedded devices. Researchers, corporations, and governments already use Peach to find vulnerabilities in hardware. This course will focus on using Peach to target embedded devices and collect information from the device in the event of a crash.
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About
python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Developers in search a solution to manage their fuzzing testing processes
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Audience
Users requiring a fuzzing engine to analyze their code and applications
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Audience
Researchers and organizations in need of a tool to find vulnerabilities in hardware
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Audience
Developers searching for a solution offering a library to write SQL queries
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle
United States
google.github.io/clusterfuzz/
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Company InformationLLVM Project
Founded: 2003
llvm.org/docs/LibFuzzer.html
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Company InformationPeach Tech
Founded: 2004
United States
peachtech.gitlab.io/peach-fuzzer-community/
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Company InformationPython Software Foundation
United States
pypi.org/project/python-sql/
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Categories |
Categories |
Categories |
Categories |
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Integrations
.NET
Atheris
C
C++
ClusterFuzz
Domino Enterprise MLOps Platform
Firebase
Fuzzbuzz
GitLab
Google ClusterFuzz
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Integrations
.NET
Atheris
C
C++
ClusterFuzz
Domino Enterprise MLOps Platform
Firebase
Fuzzbuzz
GitLab
Google ClusterFuzz
|
Integrations
.NET
Atheris
C
C++
ClusterFuzz
Domino Enterprise MLOps Platform
Firebase
Fuzzbuzz
GitLab
Google ClusterFuzz
|
Integrations
.NET
Atheris
C
C++
ClusterFuzz
Domino Enterprise MLOps Platform
Firebase
Fuzzbuzz
GitLab
Google ClusterFuzz
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