Posts
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h8mail
Email OSINT & Password breach hunting tool, locally or using premium services. Supports chasing down related email
Tags: #python • osint • email
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TikTokAPI-Python
TikTok API Python Wrapper
This is an unofficial TikTok Api python wrapper. I have an App using this API, and thus will constantly keep updating this wrapper
This implementation is inspired by TikTokApi, but runs faster.Tags: #python • tiktok • tiktok-api
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Watcher
Watcher - Open Source Cybersecurity Threat Hunting Platform. Developed with Django & React JS.
- Detecting emerging cybersecurity trends like new vulnerabilities, malwares… Via social networks & other RSS feeds (www.cert.ssi.gouv.fr, www.cert.europa.eu, www.us-cert.gov, www.cyber.gov.au…).
- Monitor for information leaks, for example in Pastebin & other IT content exchange websites (stackoverflow, github, gitlab, bitbucket, apkmirror, npm…).
- Monitor malicious domain names for changes (IPs, mail/MX records, web pages using TLSH).
- Detecting suspicious domain names targeting your organisation, using:
- dnstwist algorithm.
- Certificate transparency stream: certstream
Useful as a bundle regrouping threat hunting/intelligence automated features.
Tags: #python • cybersecurity • threat-hunting
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phpmemadmin
Bringing Memcached to the web.
- Features
- Requirements
- Philosophy
- Installation
- Screenshots
- Documentation
- Versioning
- Roadmap
- Security-Issues
- License »
Tags: #php • dashboard • memcached
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PassGAN
A Deep Learning Approach for Password Guessing (https://arxiv.org/abs/1709.00440)
This repository contains code for the PassGAN: A Deep Learning Approach for Password Guessing paper.
The model from PassGAN is taken from Improved Training of Wasserstein GANs and it is assumed that the authors of PassGAN used the improved_wgan_training tensorflow implementation in their work. For this reason, I have modified that reference implementation in this repository to make it easy to train (
train.py) and sample (sample.py) from. This repo contributes:- A command-line interface
- A pretrained PassGAN model trained on the RockYou dataset
Tags: #python • password-cracking • machine-learning
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riteway
Simple, readable, helpful unit tests.
Simple, readable, helpful unit tests.
- Readable
- Isolated/Integrated
- Thorough
- Explicit
RITEway forces you to write Readable, Isolated, and Explicit tests, because that’s the only way you can use the API. It also makes it easier to be thorough by making test assertions so simple that you’ll want to write more of them.
There are 5 questions every unit test must answer. RITEWay forces you to answer them.
- What is the unit under test (module, function, class, whatever)?
- What should it do? (Prose description)
- What was the actual output?
- What was the expected output?
- How do you reproduce the failure?
Tags: #javascript
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OpenNMT-tf
Neural machine translation and sequence learning using TensorFlow
OpenNMT-tf is a general purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support:
- sequence to sequence mapping
- sequence tagging
- sequence classification
- language modeling
The project is production-oriented and comes with backward compatibility guarantees.
Tags: #python • neural-machine-translation • tensorflow
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Self-Driving-Car-in-Video-Games
A deep neural network that learns to drive in video games
We provide pretrained T.E.D.D. 1104 models that you can use for real-time inference :)
The models are trained using 130 GB of human labelled data.
The model has been trained in first-person-view with a route to follow in the minimap.
The model has learned to drive a large variety of vehicles in different weather conditions (Sun, night, sunny, rain…). See Software and HOW-TO Section for instructions on how run the models.Tags: #python • pytorch • self-driving-car
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Leonids
A Particle System for standard Android UI: http://plattysoft.github.io/Leonids/
Leonids is available in jcenter as well as a jar file to fit both Android Studio and Eclipse.
Tags: #java
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core
Source Code for dotCMS Headless/Hybrid Content Management System
dotCMS comes in multiple editions and as such is dual licensed. The dotCMS Community Edition is licensed under the GPL 3.0 and is freely available for download, customization and deployment for use within organizations of all stripes. dotCMS Enterprise Editions (EE) adds a number of enterprise features and is available via a supported, indemnified commercial license from dotCMS. For the differences between the editions, see the feature page.
Tags: #java • dotcms • cloud
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