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Description
Echidna is a Haskell-based tool created for fuzzing and property-based testing of Ethereum smart contracts. It employs advanced grammar-driven fuzzing strategies that leverage a contract's ABI to challenge user-defined predicates or Solidity assertions. Designed with a focus on modularity, Echidna allows for easy extensions to incorporate new mutations or to target specific contracts under particular conditions. The tool generates inputs that are specifically adapted to your existing codebase, and it offers optional features for corpus collection, mutation, and coverage guidance to uncover more elusive bugs. It utilizes Slither to extract critical information prior to launching the fuzzing process, ensuring a more effective campaign. With source code integration, Echidna can pinpoint which lines of code are exercised during testing, and it provides an interactive terminal UI along with text-only or JSON output formats. Additionally, it includes automatic test case minimization for efficient triage and integrates seamlessly into the development workflow. The tool also reports maximum gas usage during fuzzing activities and supports complex contract initialization through Etheno and Truffle, enhancing its usability for developers. Ultimately, Echidna stands out as a robust solution for ensuring the reliability and security of Ethereum smart contracts.
Description
Syzkaller functions as an unsupervised, coverage-guided fuzzer aimed at exploring vulnerabilities within kernel environments, offering support for various operating systems such as FreeBSD, Fuchsia, gVisor, Linux, NetBSD, OpenBSD, and Windows. Originally designed with a focus on fuzzing the Linux kernel, its capabilities have been expanded to encompass additional operating systems over time. When a kernel crash is identified within one of the virtual machines, syzkaller promptly initiates the reproduction of that crash. By default, it operates using four virtual machines for this reproduction process and subsequently works to minimize the program responsible for the crash. This reproduction phase can temporarily halt fuzzing activities, as all VMs may be occupied with reproducing the identified issues. The duration for reproducing a single crash can vary significantly, ranging from mere minutes to potentially an hour, depending on the complexity and reproducibility of the crash event. This ability to minimize and analyze crashes enhances the overall effectiveness of the fuzzing process, allowing for better identification of vulnerabilities in the kernel.
API Access
Has API
API Access
Has API
Integrations
Docker
Etheno
Ethereum
FreeBSD
Fuchsia Service Maintenance Software
GitHub
Haskell
Homebrew
JSON
NetBSD
Integrations
Docker
Etheno
Ethereum
FreeBSD
Fuchsia Service Maintenance Software
GitHub
Haskell
Homebrew
JSON
NetBSD
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
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
Crytic
Website
github.com/crytic/echidna
Vendor Details
Company Name
Country
United States
Website
github.com/google/syzkaller