We created this Green Belt path for developers coding in R. It includes our standard 13 Green Belt Secure Development lesson with the addition of 11nR-specific modules. Each of our lessons are short and conclude with a brief ten question assessment. The learning module length is purposeful – they are perfect for filling gaps in a developer’s day while code is deploying.
Secure Development Core Lesson Modules
Intro to Secure Development
The definition of secure development and it’s pieces. Each developer has secure development responsibilities. Secure development starts and ends with the developer. Your software, hardware, and infrastructure are only as safe as you make them. Developers are the first line of defense.
The need for secure coding, what are secure coding standards and how does a developer use them, and the potential dangers of Stack Overflow. Languages are complex. Secure coding is about creating code that is correct and secure.
Secure Coding Best Practices: Part 1
Explore the OWASP Proactive Controls, including Define Security Requirements, Leverage Security Frameworks and Libraries, Secure Database Access, Encode and Escape Data, and Validate All Inputs. OWASP Proactive Controls is security information written for developers, by developers.
Secure Coding Best Practices: Part 2
Explore the OWASP Proactive Controls, including Enforce Access Control, Protect Data Everywhere, Implement Security Logging and Monitoring, and Handle All Errors and Exceptions. OWASP Proactive Controls is security information written for developers, by developers.
In this module, we explain how a languages type system is categorized and what the main categories are. We discuss the difference between static and dynamic languages as well as weak and strongly typed languages.
Securing the Development Environment
The threats that your development environment faces, how to reduce development environment risk, and the ten tips to secure your development environment. Development environment threats are real and following simple tips to secure your development environment can significantly reduce your exposure.
Protecting your Code Repository
Why you need to protect your code repository, the security challenges in choosing a repository, the impact of not protecting access credentials and separating secrets in the source code. Your code is your product or application. If it is left unsecured, it could fall into the hands of a competitor.
Producing a Clean, Maintainable, & Secure Code Culture
The sources of complexity in software that led to security vulnerabilities and the twelve laws that act as the foundation for a clean, maintainable, and secure code culture. Developers must strive for secure code. Secure code is both clean and maintainable.
Potential security threats are impacting your release and deployment process and ways to improve the security of your release and deployment process. The release and deployment process is how our code gets delivered to our customers. The introduction of an unauthorized piece of code by an attacker could be devastating.
Designing a Secure App or Product
The four pillars of a secure application or product, secure application or product decisions, and the categories of the design of a secure application or product. A new application or product deserves a secure design. Security becomes a reality through careful design choices.
Thinking Like A Penetration Tester
The tools and methodologies to help a developer think like a penetration tester, how penetration testers use browsers and intercepting proxies, testing, fuzzing, and reverse engineering, and applying the knowledge of these topics to your world as a developer. Developers generally focus on the build; to better secure your applications, products, and systems, think like one who breaks.
Secure Design Principles in Action: Part 1
The economy of mechanism, secure the weakest link, establish trust boundaries, defense in-depth, don’t reinvent the wheel, usable security and default deny. Secure design principles require action to achieve “secure by design.”
Secure Design Principles in Action: Part 2
In this module, we explore secure design principles such as minimizing the attack surface, fail securely, least privileged, separation of duties, do not trust services/ infrastructure, and secure defaults. Employing a common understanding of secure design principles encourages secure design, and secure design equals fewer vulnerabilities.
Secure Coding with R
Green Belt Path
The importance of security in the life of the data scientist, the path towards focusing on security in data science, and the security capabilities that exist within the R language and the Shiny application framework.
The different types of threats that impact R and data science and the consequences of a successful attack scenario for each specific threat.
Secure Coding with R | Part 1
Defensive programming and secure coding and the five failures of defensive programming. Introduce safe coding guidelines for R, including document your code, validate input, keep functions short and sweet, refer to external functions explicitly, and never use require().
Secure Coding with R | Part 2
Continue our exploration of safe coding guidelines for R, including eval() is evil, proactively manage dependencies, use style and code quality tools.
Secure Coding with R | Part 3
Complete our exploration of safe coding guidelines for R, including create projects as packages, read and write data securely, never allow the system() or system2() with user input, avoid using dangerous functions, and log messages, warnings, and errors.
The threats against third-party and open-source R packages and explore the available defenses to counter those threats.
Security Best Practices for R | Part 1
The system-level security features that can improve the security of your R services. The risk when downloading data from unknown sources and recognize how R security best practices assist in building a more secure application.
Security Best Practices for R | Part 2
How to secure storage buckets and secrets within an R application and the advantages of using a linter for static analysis of your R code, and how to use tools to improve code security and quality.
Securing Shiny Apps | Part 1
Explore how defensive programming and secure coding impact Shiny applications. We also discuss the different exposure levels of a Shiny application based on public, private, or local, and begin our deep dive into secure coding guidance specific to R with Shiny, including practice input validation and protection against XSS, be cautious with file upload capabilities, and watch out for data leakage when you serve data back to your users.
Securing Shiny Apps | Part 2
Complete the deep dive into secure coding guidance specific to R with Shiny, including prevent SQL and command injection, evaluate remote applications before loading them onto your server, and protect sensitive information from bookmarks and error messages.
The three server options for deploying Shiny applications and each one’s security capabilities. We walk through the steps to harden the operating system of a Shiny Server, and the specific steps to harden the Shiny application server.