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What is hevm?

The hevm project is a specialized version of the Ethereum Virtual Machine (EVM) that focuses on symbolic execution, unit testing, and the debugging of smart contracts. Developed by DappHub, it works flawlessly with the tools provided by the same creators. The hevm command line interface allows users to execute smart contracts symbolically, perform unit tests, and interactively debug contracts while showing the corresponding Solidity source code, as well as execute any arbitrary EVM code. It enables calculations to be performed either using a local state set up within a testing framework or by accessing live networks through RPC calls. Users can start symbolic execution with defined parameters to find assertion violations and have the flexibility to customize certain function signature arguments while leaving others as abstract. Importantly, hevm employs an eager approach to symbolic execution, aiming to investigate all branches of the program right from the outset. This thorough methodology significantly improves the reliability and robustness of the processes involved in smart contract development and testing. Moreover, the integration of hevm with other DappHub tools enhances the overall development experience for blockchain developers.

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

Ethereum
Solidity

Integrations Supported

Docker
Go
JSON

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

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

DappHub

Company Website

github.com/dapphub/dapptools/blob/master/src/hevm/README.md

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

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