LibFuzzer

LibFuzzer

LLVM Project
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About

Assess your marketing data & identify opportunities for immediate improvement. A complete report of the existing situation. Analyze your missing information & determine your exact requirements for complete coverage of your target market. Fill in the gaps and source the new contact data you need for accurate targeting & segmentation. High performance results delivered. Reports, metrics and processes designed perfectly for ongoing accuracy and consistency. A step by step approach to tackle this Big Data task. Developed from over 250 years of combined experience with digital marketing campaigns & technologies. Quick wins and fast turnarounds are engineered into the step by step process. Delivering a clear and easy to use action plan. Improved delivery rates and CTR’s, Increase of inbound leads; Complete coverage of your target market, decision makers and influencers. Marketing Automation & CRM, technologies that house the data and drive the campaigns.

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.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Not Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Companies and businesses looking for a software solution to assess marketing data and opportunities for improvement

Audience

Users requiring a fuzzing engine to analyze their code and applications

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

DataReef
Founded: 2002
United States
mydatareef.com

Company Information

LLVM Project
Founded: 2003
llvm.org/docs/LibFuzzer.html

Alternatives

Alternatives

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afl-unicorn

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Atheris

Atheris

Google
campaignViz

campaignViz

VizExplorer
Jazzer

Jazzer

Code Intelligence
DataMax

DataMax

Digiterre
Honggfuzz

Honggfuzz

Google
TargetEveryOne

TargetEveryOne

Target Everyone

Categories

Big Data Supported

Categories

Fuzz Testing Supported

Integrations

Atheris Not Supported
C Not Supported
C++ Not Supported
ClusterFuzz Not Supported
Fuzzbuzz Not Supported
Google ClusterFuzz Not Supported
Jazzer Not Supported

Integrations

Atheris Supported
C Supported
C++ Supported
ClusterFuzz Supported
Fuzzbuzz Supported
Google ClusterFuzz Supported
Jazzer Supported
Claim DataReef and update features and information
Claim DataReef and update features and information
Claim LibFuzzer and update features and information
Claim LibFuzzer and update features and information