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features
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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

The foundational aspect of our immunotherapy approach lies in our comprehension of antigens and neoantigens, particularly in identifying which variations will be transcribed, translated, processed, and subsequently displayed on the surface of cells via Human leukocyte antigen (HLA) molecules, thus making them recognizable to T cells. We achieve this by employing Gritstone EDGETM, a unique platform powered by machine learning. Creating cancer immunotherapies that incorporate tumor-specific neoantigens proves challenging, mainly because tumors consist of numerous mutations, yet only a fraction of these lead to genuine tumor-specific neoantigens. To tackle this complexity, we have developed EDGE's cutting-edge integrated neural network model, trained with millions of data points gathered from a diverse range of tumor and normal tissue samples across various patient ancestries. This extensive training allows us to enhance the accuracy of neoantigen identification and improve the effectiveness of our immunotherapy strategies.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Docker Yes 
Etheno Yes 
Ethereum Yes 
GitHub Yes 
Haskell Yes 
Homebrew Yes 
JSON Yes 
Nix Yes 
Solidity Yes 

Integrations

Docker No 
Etheno No 
Ethereum No 
GitHub No 
Haskell No 
Homebrew No 
JSON No 
Nix No 
Solidity No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Crytic

Website

github.com/crytic/echidna

Vendor Details

Company Name

Gritstone bio

Founded

2015

Country

United States

Website

gritstonebio.com/scientific-platform/

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Product Features

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