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Description

API Fuzzer is a tool designed to perform fuzz-testing on attributes by employing prevalent penetration testing methods while identifying potential vulnerabilities. By taking an API request as its input, the API Fuzzer gem effectively outputs a list of possible vulnerabilities inherent in the API, which may include risks such as cross-site scripting, SQL injection, blind SQL injection, XML external entity vulnerabilities, insecure direct object references (IDOR), issues with API rate limiting, open redirect vulnerabilities, information disclosure flaws, information leakage through headers, and cross-site request forgery vulnerabilities. This comprehensive evaluation helps developers enhance the security of their APIs by pinpointing critical areas that require attention and remediation.

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.

Description

Radamsa serves as a robust test case generator specifically designed for robustness testing and fuzzing, aimed at evaluating how resilient a program is against malformed and potentially harmful inputs. By analyzing sample files containing valid data, it produces a variety of uniquely altered outputs that challenge the software's stability. One of the standout features of Radamsa is its proven track record in identifying numerous bugs in significant programs, alongside its straightforward scriptability and ease of deployment. Fuzzing, a key technique in uncovering unexpected program behaviors, involves exposing the software to a wide range of input types to observe the resultant actions. This process is divided into two main components: sourcing the diverse inputs and analyzing the outcomes, with Radamsa effectively addressing the first component, while a brief shell script generally handles the latter. Testers often possess a general understanding of potential failures and aim to validate whether those concerns are warranted through this method. Ultimately, Radamsa not only simplifies the testing process but also enhances the reliability of software applications by revealing hidden vulnerabilities.

API Access

Has API

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Screenshots View All

Integrations

Atheris
C
C++
ClusterFuzz
FreeBSD
Fuzzbuzz
Git
Google ClusterFuzz
Jazzer
Make
OpenBSD
Ruby

Integrations

Atheris
C
C++
ClusterFuzz
FreeBSD
Fuzzbuzz
Git
Google ClusterFuzz
Jazzer
Make
OpenBSD
Ruby

Integrations

Atheris
C
C++
ClusterFuzz
FreeBSD
Fuzzbuzz
Git
Google ClusterFuzz
Jazzer
Make
OpenBSD
Ruby

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
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

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

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

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Fuzzapi

Website

github.com/Fuzzapi/API-fuzzer

Vendor Details

Company Name

LLVM Project

Founded

2003

Website

llvm.org/docs/LibFuzzer.html

Vendor Details

Company Name

Aki Helin

Website

gitlab.com/akihe/radamsa

Product Features

Product Features

Product Features

Alternatives

Alternatives

Atheris Reviews

Atheris

Google

Alternatives

afl-unicorn Reviews

afl-unicorn

Battelle
LibFuzzer Reviews

LibFuzzer

LLVM Project
go-fuzz Reviews

go-fuzz

dvyukov
ClusterFuzz Reviews

ClusterFuzz

Google
Jazzer Reviews

Jazzer

Code Intelligence
go-fuzz Reviews

go-fuzz

dvyukov