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  1. GoldenEye is a Python 3 app for SECURITY TESTING PURPOSES ONLY! GoldenEye is an HTTP DoS Test Tool. Attack Vector exploited: HTTP Keep Alive + NoCache

  2. GoldenEye is a functional simulator with fault injection capabilities for common and emerging numerical formats, implemented for the PyTorch deep learning framework.

  3. GoldenEye is a functional simulator with fault injection capabilities for common and emerging numerical formats, implemented for the PyTorch deep learning framework.

  4. May 10, 2023 · Goldeneye is an open-source tool, so you can download it from GitHub free of cost. Goldeneye can be used to perform DDoS attacks on any webserver. Installation . Step 1: Open your Kali Linux and then Open your Terminal. Use the following command to install the tool by cloning the GitHub repository. git clone https://github.com/jseidl/GoldenEye.git

  5. GoldenEye Layer 7 (KeepAlive+NoCache) DoS Test Tool - GoldenEye/goldeneye.py at master · jseidl/GoldenEye

  6. GoldenEye is a HTTP DoS Test Tool. This tool can be used to test if a site is susceptible to Deny of Service (DoS) attacks. Is possible to open several parallel connections against a URL to check if the web server can be compromised.

  7. A decompilation of Goldeneye 007 brought to you by a bunch of clever folks. (MIRROR of https://gitlab.com/kholdfuzion/goldeneye_src) - n64decomp/007.

  8. Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset. - goldeneye/goldeneye.py at master · tsabsch/goldeneye

  9. GoldenEye is a Full Stack framework written in .NET. The main goal of GoldenEye is to speed up your development process. It gathers most widely used frameworks in .NET world and pack them into a simple bootstrap Nuget packages. It also provide set of base classes, helpers, extensions that will help you with your daily work. What do I get?

  10. In addition to being an extensible playground for novel data format exploration, GoldenEye presents a unified framework for evaluating number formats and their effect on DNN classification accuracy.