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.

11 modules | 2 hrs 32 min | Green Belt Level
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Example of Secure Coding with R Concepts

  • Shiny application framework
  • 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
  • Three server options for deploying Shiny applications

What's Included?

We created this Green Belt path for developers coding in R. 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

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