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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Our platform uses a variety of security techniques, including feedback-based fuzz testing and coverage-guided fuzz testing, in order to generate millions upon millions of test cases that trigger difficult-to-find bugs deep in your application. This white-box approach helps to prevent edge cases and speed up development. Advanced fuzzing engines produce inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Only uncover true vulnerabilities. You will need the stack trace and input to prove that you can reproduce errors reliably every time. AI white-box testing is based on data from all previous tests and can continuously learn the inner workings of your application. This allows you to trigger security-critical bugs with increasing precision.

Description

LibFuzzer serves as an in-process, coverage-guided engine for evolutionary fuzzing. By being linked directly with the library under examination, it injects fuzzed inputs through a designated entry point, or target function, allowing it to monitor the code paths that are executed while creating variations of the input data to enhance code coverage. The coverage data is obtained through LLVM’s SanitizerCoverage instrumentation, ensuring that users have detailed insights into the testing process. Notably, LibFuzzer continues to receive support, with critical bugs addressed as they arise. To begin utilizing LibFuzzer with a library, one must first create a fuzz target—this function receives a byte array and interacts with the API being tested in a meaningful way. Importantly, this fuzz target operates independently of LibFuzzer, which facilitates its use alongside other fuzzing tools such as AFL or Radamsa, thereby providing versatility in testing strategies. Furthermore, the ability to leverage multiple fuzzing engines can lead to more robust testing outcomes and clearer insights into the library's vulnerabilities.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C
C++
Apache Maven
Atheris
CLion
CircleCI
ClusterFuzz
Docker
Fuzzbuzz
GitHub
GitLab
Gradle
JUnit
Java
JavaScript
Jazzer
Jenkins
Kubernetes
Vim
Visual Studio

Integrations

C
C++
Apache Maven
Atheris
CLion
CircleCI
ClusterFuzz
Docker
Fuzzbuzz
GitHub
GitLab
Gradle
JUnit
Java
JavaScript
Jazzer
Jenkins
Kubernetes
Vim
Visual Studio

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Code Intelligence

Country

Germany

Website

www.code-intelligence.com

Vendor Details

Company Name

LLVM Project

Founded

2003

Website

llvm.org/docs/LibFuzzer.html

Product Features

Application Security

Analytics / Reporting
Open Source Component Monitoring
Source Code Analysis
Third-Party Tools Integration
Training Resources
Vulnerability Detection
Vulnerability Remediation

Product Features

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