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features
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support

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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

Fuzz testing, commonly referred to as fuzzing, is a technique used in software testing that aims to discover implementation errors by injecting malformed or semi-malformed data in an automated way. For example, consider a scenario involving an integer variable within a program that captures a user's selection among three questions; the user's choice can be represented by the integers 0, 1, or 2, resulting in three distinct cases. Since integers are typically stored as fixed-size variables, a failure to implement the default switch case securely could lead to program crashes and various traditional security vulnerabilities. Fuzzing serves as an automated method for uncovering software implementation issues, enabling the identification of bugs when they occur. A fuzzer is a specialized tool designed to automatically inject semi-random data into the program stack, aiding in the detection of anomalies. The process of generating this data involves the use of generators, while the identification of vulnerabilities often depends on debugging tools that can analyze the program's behavior under the influence of the injected data. These generators typically utilize a mixture of established static fuzzing vectors to enhance the testing process, ultimately contributing to more robust software development practices.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Maven
C
C++
CI Fuzz
CLion
CircleCI
Docker
GitLab
Go
Gradle
JUnit
Java
JavaScript
Jenkins
Jira
Kubernetes
Travis CI
Vim
Visual Basic
Visual Studio

Integrations

Apache Maven
C
C++
CI Fuzz
CLion
CircleCI
Docker
GitLab
Go
Gradle
JUnit
Java
JavaScript
Jenkins
Jira
Kubernetes
Travis CI
Vim
Visual Basic
Visual Studio

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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

OWASP

Country

United States

Website

owasp.org/www-community/Fuzzing

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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