| INTRO | |
| I get asked regularly for good resources on AWS security. This gist collects some of these resources (docs, blogs, talks, open source tools, etc.). Feel free to suggest and contribute. | |
| Short Link: http://tiny.cc/awssecurity | |
| Official AWS Security Resources | |
| * Security Blog - http://blogs.aws.amazon.com/security/ | |
| * Security Advisories - http://aws.amazon.com/security/security-bulletins/ | |
| * Security Whitepaper (AWS Security Processes/Practices) - http://media.amazonwebservices.com/pdf/AWS_Security_Whitepaper.pdf | |
| * Security Best Practices Whitepaper - http://media.amazonwebservices.com/AWS_Security_Best_Practices.pdf |
| ''' | |
| Pure Python Borromean Ring Signatures | |
| DEPENDS ON: pip install ecdsa | |
| WARNING: THIS IS A PEDAGOGICAL IMPLEMENTATION. | |
| PERFORMANCE IS HORRIBLE AND NON-CONSTANT. | |
| CORNER CASES ARE NOT PROPERLY CHECKED. | |
| FOR THE LOVE OF GOD USE THE CODE FROM THE ELEMENTS PROJECT. | |
| https://gist.github.com/badmofo/2d6e66630e4a6748edb7 | |
| ''' | |
| from hashlib import sha256 |
| # MIT License | |
| # | |
| # Copyright (C) 2014 Jesper Borgstrup | |
| # ------------------------------------------------------------------- | |
| # Permission is hereby granted, free of charge, to any person | |
| # obtaining a copy of this software and associated documentation | |
| # files (the "Software"), to deal in the Software without restriction, | |
| # including without limitation the rights to use, copy, modify, merge, | |
| # publish, distribute, sublicense, and/or sell copies of the Software, | |
| # and to permit persons to whom the Software is furnished to do so, |
| error_page 400 404 405 =200 @40*_json; | |
| location @40*_json { | |
| default_type application/json; | |
| return 200 '{"code":"1", "message": "Not Found"}'; | |
| } | |
| error_page 500 502 503 504 =200 @50*_json; | |
| location @50*_json { |
| from btgym import BTgymEnv | |
| import IPython.display as Display | |
| import PIL.Image as Image | |
| from gym import spaces | |
| import gym | |
| import numpy as np | |
| import random |
| # Author: Kyle Kastner | |
| # License: BSD 3-Clause | |
| # Implementing http://mnemstudio.org/path-finding-q-learning-tutorial.htm | |
| # Q-learning formula from http://sarvagyavaish.github.io/FlappyBirdRL/ | |
| # Visualization based on code from Gael Varoquaux gael.varoquaux@normalesup.org | |
| # http://scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from matplotlib.collections import LineCollection |
This Gist has been transfered into a Github Repo. You'll find the most recent version here.
When creating your rules for YARA keep in mind the following guidelines in order to get the best performance from them. This guide is based on ideas and recommendations by Victor M. Alvarez and WXS.
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| // A small SSH daemon providing bash sessions | |
| // | |
| // Server: | |
| // cd my/new/dir/ | |
| // #generate server keypair | |
| // ssh-keygen -t rsa | |
| // go get -v . | |
| // go run sshd.go | |
| // | |
| // Client: |
| // Mini memory editor for Dear ImGui (to embed in your game/tools) | |
| // Animated GIF: https://twitter.com/ocornut/status/894242704317530112 | |
| // THE MEMORY EDITOR CODE HAS MOVED TO GIT: | |
| // https://github.com/ocornut/imgui_club/tree/master/imgui_memory_editor | |
| // Click "Revisions" on the Gist to see old version. |