Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Digital WarRoom Reviews & Ratings
    4.6 out of 5 stars 55 Ratings
    Company Website for Digital WarRoom
  • Forethought Reviews & Ratings
    4.3 out of 5 stars 166 Ratings
    Company Website for Forethought
  • AlsoThere Reviews & Ratings
    5.0 out of 5 stars 1 Rating
    Company Website for AlsoThere
  • TradingView Stock Widgets Reviews & Ratings
    5.0 out of 5 stars 16 Ratings
    Company Website for TradingView Stock Widgets
  • WinningBidder.com Reviews & Ratings
    4.8 out of 5 stars 165 Ratings
    Company Website for WinningBidder.com
  • Filerev Reviews & Ratings
    5.0 out of 5 stars 3 Ratings
    Company Website for Filerev
  • Bluepear Reviews & Ratings
    4.8 out of 5 stars 74 Ratings
    Company Website for Bluepear
  • Gushwork Reviews & Ratings
    4.5 out of 5 stars 29 Ratings
    Company Website for Gushwork
  • Fax.Cloud Reviews & Ratings
    5.0 out of 5 stars 1 Rating
    Company Website for Fax.Cloud
  • RaimaDB Reviews & Ratings
    4.8 out of 5 stars 12 Ratings
    Company Website for RaimaDB

What is Honggfuzz?

Honggfuzz is a sophisticated software fuzzer dedicated to improving security through its innovative fuzzing methodologies. Utilizing both evolutionary and feedback-driven approaches, it leverages software and hardware-based code coverage for optimal performance. The tool is adept at functioning within multi-process and multi-threaded frameworks, enabling users to fully utilize their CPU capabilities without the need for launching multiple instances of the fuzzer. Sharing and refining the file corpus across all fuzzing processes significantly boosts efficiency. When the persistent fuzzing mode is enabled, Honggfuzz showcases exceptional speed, capable of running a simple or empty LLVMFuzzerTestOneInput function at an astonishing rate of up to one million iterations per second on contemporary CPUs. It has a strong track record of uncovering security vulnerabilities, including the significant identification of the sole critical vulnerability in OpenSSL thus far. In contrast to other fuzzing solutions, Honggfuzz can recognize and report on hijacked or ignored signals resulting from crashes, enhancing its utility in pinpointing obscure issues within fuzzed applications. With its comprehensive features and capabilities, Honggfuzz stands as an invaluable resource for security researchers striving to reveal hidden weaknesses in software architectures. This makes it not only a powerful tool for testing but also a crucial component in the ongoing battle against software vulnerabilities.

What is Ffuf?

Ffuf is an efficient web fuzzer created using Go, enabling users to perform scans on active hosts through various scenarios and lessons, which can be run locally via a Docker container or through a web-based platform. It includes capabilities for virtual host discovery that do not rely on DNS records, enhancing its versatility. To make the most of Ffuf, users are required to supply a wordlist with the desired input values for testing. Multiple wordlists can be utilized by specifying them directly in the command line, and when employing more than one, it is crucial to assign a unique keyword for proper management. Ffuf begins by testing the first entry of the initial wordlist against all entries in the additional wordlist, progressing to the next entry of the first wordlist and continuing this sequence until every possible combination has been examined. This systematic approach guarantees comprehensive testing of potential inputs. Additionally, Ffuf provides a range of options for further tailoring the requests made during the fuzzing process, allowing users to fine-tune their assessments. By taking advantage of these features, users can significantly enhance the effectiveness of their web vulnerability evaluations while gaining deeper insights into their applications' security.

Media

Media

Integrations Supported

ClusterFuzz
Cygwin
FreeBSD
Google ClusterFuzz
NetBSD
OpenSSL

Integrations Supported

Docker
Go
JSON

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

Android
Windows
Mac
Linux

Supported Platforms

SaaS
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Company Location

United States

Company Website

github.com/google/honggfuzz

Company Facts

Organization Name

Ffuf

Company Website

github.com/ffuf/ffuf

Categories and Features

Fuzz Testing

Not specified

Categories and Features

Fuzz Testing

Not specified

Popular Alternatives

LibFuzzer Reviews & Ratings

LibFuzzer

LLVM Project

Popular Alternatives

Atheris Reviews & Ratings

Atheris

Google
Accent EXCEL Password Recovery Reviews & Ratings

Accent EXCEL Password Recovery

Passcovery Co. Ltd.