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Building and Automating Penetration Testing Labs in the Cloud

Building and Automating Penetration Testing Labs in the Cloud

By : Joshua Arvin Lat
4.8 (13)
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Building and Automating Penetration Testing Labs in the Cloud

Building and Automating Penetration Testing Labs in the Cloud

4.8 (13)
By: Joshua Arvin Lat

Overview of this book

The significant increase in the number of cloud-related threats and issues has led to a surge in the demand for cloud security professionals. This book will help you set up vulnerable-by-design environments in the cloud to minimize the risks involved while learning all about cloud penetration testing and ethical hacking. This step-by-step guide begins by helping you design and build penetration testing labs that mimic modern cloud environments running on AWS, Azure, and Google Cloud Platform (GCP). Next, you’ll find out how to use infrastructure as code (IaC) solutions to manage a variety of lab environments in the cloud. As you advance, you’ll discover how generative AI tools, such as ChatGPT, can be leveraged to accelerate the preparation of IaC templates and configurations. You’ll also learn how to validate vulnerabilities by exploiting misconfigurations and vulnerabilities using various penetration testing tools and techniques. Finally, you’ll explore several practical strategies for managing the complexity, cost, and risks involved when dealing with penetration testing lab environments in the cloud. By the end of this penetration testing book, you’ll be able to design and build cost-effective vulnerable cloud lab environments where you can experiment and practice different types of attacks and penetration testing techniques.
Table of Contents (15 chapters)
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1
Part 1: A Gentle Introduction to Vulnerable-by-Design Environments
5
Part 2: Setting Up Isolated Penetration Testing Lab Environments in the Cloud
9
Part 3: Exploring Advanced Strategies and Best Practices in Lab Environment Design

Recognizing the impact of cloud computing on the cybersecurity landscape

In the past, companies had to host their applications primarily in their data centers. Due to the operational overhead of managing their own data centers, most businesses have considered migrating their data and their workloads to the cloud. Some organizations have moved all their applications and data to the cloud, while others use a hybrid cloud architecture to host their applications in both on-premises data centers and in the cloud. Cloud computing has allowed companies to do the following:

  • Ensure continuous operations: High availability in the cloud ensures that applications and services remain accessible and operational, even in the event of failures or disruptions. By leveraging redundancy and fault-tolerant architectures offered by cloud providers, downtime is minimized, and uninterrupted access to resources is maintained.
  • Save money: No hardware infrastructure investment is needed to get started as cloud resources can be created and deleted within seconds or minutes. In addition to this, cloud platforms generally have a pay-per-use model for the usage of cloud resources.
  • Easily manage application workloads: Application workloads in the cloud can be managed remotely. In addition to this, resources can be scaled up and down easily, depending on what the business needs.
  • Easily manage data: Managing data becomes more streamlined and convenient in the cloud environment due to the availability of a wide range of services, features, and capabilities. Additionally, the virtually unlimited storage capacity offered by the cloud eliminates concerns related to handling large files. This enhanced data management capability in the cloud contributes to improved efficiency and scalability for companies.
  • Automate relevant processes: Building automated pipelines and workflows in the cloud is easier since most of the cloud services can be managed through application programming interfaces (APIs) and software development kits (SDKs).

With more companies storing their data in the cloud, there has been a significant increase in cloud attacks in the last couple of years. The attack surface has changed due to the rise of cloud computing, and along with it, the types of attacks have changed. Hackers can take advantage of vulnerable and misconfigured cloud resources, which could end up having sensitive data stored in the cloud stolen.

What do we mean by attack surface?

Attack surface refers to the collective set of potential vulnerabilities within a system that can be exploited by attackers. It encompasses various elements, including network interfaces, APIs, user access points, operating systems, and deployed cloud resources. Understanding and managing the attack surface is crucial for assessing and mitigating security risks in the cloud as it allows organizations to identify and address potential weak points that could be targeted by malicious actors.

With this in mind, here is a quick list of relevant cyberattacks on cloud-based data and applications:

  • Attacks on vulnerable application servers and misconfigured cloud storage resources: Attacks on vulnerable and misconfigured cloud resources such as APIs, virtual machines, CI/CD pipelines, and storage resources have resulted in serious data breaches around the world. Identities and information stolen from data breaches are used for identity theft and phishing.
  • Ransomware attacks in the cloud: Sensitive data stored in the cloud is constantly being targeted by hackers. Ransomware victims are generally asked to pay the ransom in Bitcoin or other cryptocurrencies. Bitcoin and other cryptocurrencies let users maintain their anonymity. This, along with other techniques, makes it hard for authorities to track down ransomware hackers.
  • Cloud account hijacking: Once a hacker takes over an organization’s cloud account, the hacker can freely spin up resources, access sensitive files, and use resources inside the account to attack other companies and accounts.
  • Distributed Denial-of-Service (DDoS) and Denial-of-Wallet (DoW) attacks: During a DDoS attack, an attacker seeks to make an online service unavailable by overwhelming and flooding deployed cloud resources with generated traffic. During a DoW attack, similar techniques are used to inflict financial damage (due to a large bill).

Over the years, the quantity and quality of tools focusing on cloud security have increased as cloud security threats have evolved and become more widespread. More security tools and utilities became available as the number of disclosed vulnerabilities increased every year. These tools ranged from simple scripts to sophisticated frameworks and modules that can be configured to suit the needs of an attacker. Security professionals have seen tools and products evolve over time as well. In the past, cloud security products needed to be installed and set up by the internal teams of companies. These past few years, more managed cloud-based tools and services became available, most of which can be used immediately with minimal configuration. Here are some of the more recent security solutions that have become available for cloud security:

  • Various offensive security cloud tools and frameworks
  • Agentless vulnerability assessment tools for virtual machines in the cloud
  • Vulnerability assessment tools for container images
  • Vulnerability assessment tools and services for serverless compute resources
  • Machine learning-powered code security scanner tools and services
  • Cloud network security audit tools
  • Managed cloud firewalls
  • Managed cloud threat detection services
  • Artificial intelligence-powered security tools

At this point, we should have a better understanding of how cloud computing has shaped and influenced the cybersecurity landscape. In the next section, we will dive deeper into how modern applications are designed, developed, and deployed in the cloud.

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