Scanner

Scanner to detect the Spring4Shell vulnerability on input URLs

Scanner to detect the Spring4Shell vulnerability on input URLs Note: Detection Script has been tested on applications deployed using Apache Tomcat Server Prerequisite’s python3 python3 -m pip install -r requirements.txt Usage python3 detect.py –help usage: detect.py [-h] [–file FILE] –url URL [–debug] [–get] [–post] [–ver] options: -h, –help show this help message and exit –file FILE File containing Form Endpoints –url URL target Form Endpoints –debug Print errors –get Use Get Method –post Use Post Method –ver Perform    

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Robot

Working model of an industrial robot arm

This is the second version of my 6 axis robotic arm. The first version had a lot of mechanical design issues, so i stoped working on it before finishing the software and went to work on this one instead. It is 3D printed in PETG, uses 6 dynamixels XL330-M288-T servomotors and is controlled by a raspberry Pi, with a U2D2 communication converter between the Pi and the servo bus. you will find the python code in the “programme” directory. The […]

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Pipeline

A crossplatform Houdini project management and pipeline tool for smaller teams, students, and classrooms

A crossplatform Houdini project management and pipeline tool for smaller teams, students, and classrooms. Pyrsomes are actually colonies of small jellyfish creating a whole. I thought that was a fun way to think about group creative projects. In a way this tool helps multiple people be part of a whole, and because it’s houdini, life, mathematics and growth are common insterests of houdini artists. This was developed for my needs during my senior project using Houdini with a small team. […]

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Web

HOOK-Worm Pentest the Modern Web

HOOK-Worm Pentest the Modern Web Author: [Free.Programmer] Disclaimer: I am not responsible for any damage done using this tool. This tool should only be used for educational purposes and for penetration testing. ###Compatibility: Any platform using Python ###Requirements: Python 2.7 Modules(included): Colorama, BeautifulSoup ###Description: hook-pentester is an All-In-One Tool for Penetration Testing. This is specially programmed for Penetration Testers and Security Researchers to make their job easier, instead of launching different tools for performing different task. hook-pentester provides multiple features […]

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Graph

GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment

The official source code for “GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment”, accepted at SIGIR 2022(Short Paper). Overview Despite the success of Graph Neural Networks (GNNs) on various applications, GNNs encounter significant performance degradation when the amount of supervision signals, i.e., number of labeled nodes, is limited, which is expected as GNNs are trained solely based on the supervision obtained from the labeled nodes. On the other hand, recent self-supervised learning paradigm aims to […]

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Scanner

Full Central IoC scanner based on Loki

is a central IoC scanner based on Loki General Info This application Loki latest version and download it on all machines using a powershell script and run it then this app receives the respose from all machines and parse the feed in CSV form. Requirements Python +3.5 PyQT5 psutil pyparsing zipfile Fetch LOki Scanner download and extract the latest version on Loki and start HTTP server to deliver the executable (Loki) to all machines. Deploy Loki This step has ti […]

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Machine Learning

SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image

pip install -r requirements.txt python eval.py –dataset_name llff –root_dir /dataset/nerf_llff_data/room –N_importance 64 –img_wh 504 378 –model nerf –ckpt_path room.ckpt –timestamp test Refactoring in progress. @InProceedings{Xu_2022_SinNeRF, author = {Xu, Dejia and Jiang, Yifan and Wang, Peihao and Fan, Zhiwen and Shi, Humphrey and Wang, Zhangyang}, title = {SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image}, journal={arXiv preprint arXiv:2204.00928},    

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Natural Language Processing

Accelerated NLP pipelines for fast inference on CPU and GPU. Built with Transformers, Optimum and ONNX Runtime

Accelerated NLP pipelines for fast inference 🚀 on CPU and GPU. Built with 🤗Transformers, Optimum and ONNX runtime. Installation: With PyPI: pip install optimum-transformers Or directly from GitHub: pip install git+https://github.com/AlekseyKorshuk/optimum-transformers Usage: The pipeline API is similar to transformers pipeline with just a few differences which are explained below. Just provide the path/url to the model, and it’ll download the model if needed from the hub and automatically create onnx graph and run inference.

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End-to-End

Nix-TTS: An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation

An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation Rendi Chevi, Radityo Eko Prasojo, Alham Fikri Aji This is a repository for our paper, 🐤 Nix-TTS (Submitted to INTERSPEECH 2022). We released the pretrained models, an interactive demo, and audio samples below. [📄 Paper Link] [🤗 Interactive Demo] [📢 Audio Samples] Abstract    We propose Nix-TTS, a lightweight neural TTS (Text-to-Speech) model achieved by applying knowledge distillation to a powerful yet large-sized generative TTS teacher model. Distilling a TTS model might […]

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Computer Vision

An all-in-one toolkit for computer vision

Introduction EasyCV is an all-in-one computer vision toolbox based on PyTorch, mainly focus on self-supervised learning, image classification, metric-learning, object detection and so on. Major features SOTA SSL Algorithms EasyCV provides state-of-the-art algorithms in self-supervised learning based on contrastive learning such as SimCLR, MoCO V2, Swav, DINO and also MAE based on masked image modeling. We also provides standard benchmark tools for ssl model evaluation. Vision Transformers EasyCV aims to provide plenty vision transformer models trained either using supervised learning […]

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