LibFuzzerLLVM Project
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RadamsaAki Helin
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Related Products
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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
Radamsa is a test case generator for robustness testing or fuzzer. It is typically used to test how well a program can withstand malformed and potentially malicious inputs. It works by reading sample files of valid data and generating interestingly different outputs from them. The main selling points of Radamsa are that it has already found a slew of bugs in programs that actually matter, it is easily scriptable, and, easy to get up and running. Fuzzing is one of the techniques to find unexpected behavior in programs. The idea is simply to subject the program to various kinds of inputs and see what happens. There are two parts to this process: getting the various kinds of inputs and how to see what happens. Radamsa is a solution to the first part, and the second part is typically a short shell script. Testers usually have a more or less vague idea of what should not happen, and they try to find out if this is so.
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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
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Users requiring a fuzzing engine to analyze their code and applications
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Audience
Testers searching for a solution to find issues in their program processes and applications
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationLLVM Project
Founded: 2003
llvm.org/docs/LibFuzzer.html
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Company InformationAki Helin
gitlab.com/akihe/radamsa
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Atheris
Supported
C
Supported
C++
Supported
ClusterFuzz
Supported
FreeBSD
Not Supported
Fuzzbuzz
Supported
Git
Not Supported
Google ClusterFuzz
Supported
Jazzer
Supported
Make
Not Supported
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Integrations
Atheris
Not Supported
C
Not Supported
C++
Not Supported
ClusterFuzz
Not Supported
FreeBSD
Supported
Fuzzbuzz
Not Supported
Git
Supported
Google ClusterFuzz
Not Supported
Jazzer
Not Supported
Make
Supported
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