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
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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

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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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

DataReef
Founded: 2002
United States
mydatareef.com

Company Information

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

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Categories

Categories

Integrations

Atheris
C
C++
ClusterFuzz
Fuzzbuzz
Google ClusterFuzz
Jazzer

Integrations

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