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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

FuzzDB was developed to enhance the chances of identifying security vulnerabilities in applications through dynamic testing methods. As the first and most extensive open repository of fault injection patterns, along with predictable resource locations and regex for server response matching, it serves as an invaluable resource. This comprehensive database includes detailed lists of attack payload primitives aimed at fault injection testing. The patterns are organized by type of attack and, where applicable, by the platform, and they are known to lead to vulnerabilities such as OS command injection, directory listings, directory traversals, source code exposure, file upload bypass, authentication bypass, cross-site scripting (XSS), HTTP header CRLF injections, SQL injection, NoSQL injection, and several others. For instance, FuzzDB identifies 56 patterns that might be interpreted as a null byte, in addition to offering lists of frequently used methods and name-value pairs that can activate debugging modes. Furthermore, the resource continuously evolves as it incorporates new findings and community contributions to stay relevant against emerging threats.

Description

NeuralMould, developed by Emmi AI, is an advanced Large Engineering Model specifically designed for injection molding, setting a new benchmark in AI-driven engineering solutions by accommodating any geometry, material, and injection gate configuration within a single framework. Users can easily choose from various geometries while testing different parameters related to injection, materials, and gate placement, allowing for quick simulations of filling behavior, rapid scenario comparisons, optimization of key performance indicators, and the prevention of frozen flow fronts. The complexity of injection molding simulations arises from the necessity to conduct multi-physics calculations, which accurately model the transient flow of viscous plastics through intricately designed thin-walled shapes under high-pressure and high-temperature conditions. NeuralMould effectively captures these critical phenomena across diverse injection scenarios and mold designs, achieving results that rival traditional solvers but with significantly reduced computation times. Additionally, the model is capable of handling multi-material applications, facilitating quick prototyping, accommodating multi-gate setups, and managing a variety of processing parameters thanks to its scalable transformer-based architecture. This innovative approach uniquely positions NeuralMould as a vital tool for engineers seeking to enhance efficiency and precision in the injection molding process.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

BlackArch Linux
NoSQL
OWASP ZAP

Integrations

BlackArch Linux
NoSQL
OWASP ZAP

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

FuzzDB

Website

github.com/fuzzdb-project/fuzzdb

Vendor Details

Company Name

Emmi AI

Country

Austria

Website

www.emmi.ai/models/neuralmould

Product Features

Product Features

Engineering

2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering

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