Secure Coding with R

Explore the R threat landscape the best practices for securing R, threats against third-party and open-source R packages, as well as shiny apps and servers.

24 modules | 5 hrs 34 min | Green Belt Level
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Example of Secure Coding with R Concepts

  • A variety of threats that impact R
  • Threats against third-party and open-source R packages
  • Security improvement of R services and best practices
  • Secure storage buckets and secrets within R application
  • Defensive programming and safe coding guidelines
  • Exploration of safe coding guidelines for R
  • Variety of exposure levels of a Shiny application
  • Secure coding guidance

What's Included?

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
Intro to Secure Coding
Secure Coding Best Practices: Part 1
Secure Coding Best Practices: Part 2
Language Typing
Securing the Development Environment
Protecting your Code Repository
Producing a Clean, Maintainable, & Secure Code Culture
Secure the Release
Designing a Secure App or Product
Thinking Like A Penetration Tester
Secure Design Principles in Action: Part 1
Secure Design Principles in Action: Part 2
Secure Coding with R
Green Belt Path
Intro to R security
The R Threat Landscape
Secure Coding with R | Part 1
Secure Coding with R | Part 2
Secure Coding with R | Part 3
Third-Party R Packages
Security Best Practices for R | Part 1
Security Best Practices for R | Part 2
Securing Shiny Apps | Part 1
Securing Shiny Apps | Part 2
Securing Shiny Servers