Default Exploit's starred repositories
90DaysOfDevOps
This repository started out as a learning in public project for myself and has now become a structured learning map for many in the community. We have 3 years under our belt covering all things DevOps, including Principles, Processes, Tooling and Use Cases surrounding this vast topic.
ScoutSuite
Multi-Cloud Security Auditing Tool
php-encryption
Simple Encryption in PHP.
terraform-aws-eks-blueprints
Configure and deploy complete EKS clusters.
retail-demo-store
AWS Retail Demo Store is a sample retail web application and workshop platform demonstrating how AWS infrastructure and services can be used to build compelling customer experiences for eCommerce, retail, and digital marketing use-cases
superwerker
superwerker can help you get started with the AWS Cloud quickly without investing in consultants or devoting time to extensive research. superwerker is a free, open-source solution that lets you quickly set up an AWS Cloud environment following best practices for security and efficiency so you can focus on your core business.
cdk-eks-blueprints
AWS Quick Start Team
awskillswitch
Lambda function that streamlines containment of an AWS account compromise
eb-java-scorekeep
RESTful web API in Java with Spring that provides an HTTP interface for creating and managing game sessions and users.
threatmodel-for-aws-s3
ThreatModel for Amazon S3 - Library of all the attack scenarios on Amazon S3, and how to mitigate them following a risk-based approach
carto-selfhosted
Deploy CARTO in a self hosted environment
amazon-rekognition-custom-labels-a2i-automated-continuous-model-improvement
With Amazon Rekognition Custom Labels, you can easily build and deploy Machine Learning (ML) models to identify custom objects which are specific to your business domain in images without requiring advanced ML knowledge. When combined with Amazon Augmented AI (A2I), you can quickly integrate a ML workflow to capture and label images with a human workforce for model training. As ML lifecycle is an iterative and repetitive process, you need to implement an effective workflow that can provide for continuous model training with new data and automated deployment. Your workflow also needs to be flexible enough to allow for changes without requiring development rework as your business objectives change. Operationalizing an effective and flexible workflow can be resource intensive, especially for customers who have limited machine learning capabilities. In this post, we will use AWS Step Functions, AWS Lambda, and AWS System Manager Parameter Store to automate a configurable ML workflow for Rekognition Custom Labels and A2I. We will provide an overview of the solution and instructions to deploy it with AWS CloudFormation.
NMF-audio-to-WAV-convertor
Improved Python script to convert NMF to WAV
Threat-Alert
stackArmor's repository of AWS CloudFormation templates
kubernetes-the-hard-way
Bootstrap Kubernetes the hard way on Google Cloud Platform. No scripts.
3D_Rendering
3D Rendering for Online Cognitive Studies, a Technica Research