Видавець: Packt Publishing
Feroz Louis, Feroz Louis, Gaurav Gupta
Prakhar Prasad, Rafay Baloch
Web penetration testing is a growing, fast-moving, and absolutely critical field in information security. This book executes modern web application attacks and utilises cutting-edge hacking techniques with an enhanced knowledge of web application security.We will cover web hacking techniques so you can explore the attack vectors during penetration tests. The book encompasses the latest technologies such as OAuth 2.0, Web API testing methodologies and XML vectors used by hackers. Some lesser discussed attack vectors such as RPO (relative path overwrite), DOM clobbering, PHP Object Injection and etc. has been covered in this book.We'll explain various old school techniques in depth such as XSS, CSRF, SQL Injection through the ever-dependable SQLMap and reconnaissance. Websites nowadays provide APIs to allow integration with third party applications, thereby exposing a lot of attack surface, we cover testing of these APIs using real-life examples. This pragmatic guide will be a great benefit and will help you prepare fully secure applications.
Mastering MongoDB 3.x. An expert's guide to building fault-tolerant MongoDB applications
Alex Giamas
MongoDB has grown to become the de facto NoSQL database with millions of users—from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources.You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator.
Alex Giamas
MongoDB is the best platform for working with non-relational data and is considered to be the smartest tool for organizing data in line with business needs. The recently released MongoDB 4.x supports ACID transactions and makes the technology an asset for enterprises across the IT and fintech sectors. This book provides expertise in advanced and niche areas of managing databases (such as modeling and querying databases) along with various administration techniques in MongoDB, thereby helping you become a successful MongoDB expert. The book helps you understand how the newly added capabilities function with the help of some interesting examples and large datasets. You will dive deeper into niche areas such as high-performance configurations, optimizing SQL statements, configuring large-scale sharded clusters, and many more. You will also master best practices in overcoming database failover, and master recovery and backup procedures for database security.By the end of the book, you will have gained a practical understanding of administering database applications both on premises and on the cloud; you will also be able to scale database applications across all servers.
Alex Giamas
MongoDB is a leading non-relational database. This book covers all the major features of MongoDB including the latest version 6. MongoDB 6.x adds many new features and expands on existing ones such as aggregation, indexing, replication, sharding and MongoDB Atlas tools. Some of the MongoDB Atlas tools that you will master include Atlas dedicated clusters and Serverless, Atlas Search, Charts, Realm Application Services/Sync, Compass, Cloud Manager and Data Lake.By getting hands-on working with code using realistic use cases, you will master the art of modeling, shaping and querying your data and become the MongoDB oracle for the business. You will focus on broadly used and niche areas such as optimizing queries, configuring large-scale clusters, configuring your cluster for high performance and availability and many more. Later, you will become proficient in auditing, monitoring, and securing your clusters using a structured and organized approach.By the end of this book, you will have grasped all the practical understanding needed to design, develop, administer and scale MongoDB-based database applications both on premises and on the cloud.
Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak...
Mastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB’s architecture and developer tools, guiding you through the process of connecting to databases seamlessly.This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today’s organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0’s deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers.By the end of this book, you’ll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You’ll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.
Mastering .NET Machine Learning. Use machine learning in your .NET applications
Jamie Dixon
.Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines.This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions.You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results.Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly.
David Salter, Diego Fontan, David Salter