Safely Mask Sensitive Data in Terraform with Data Source "External" and Shell Scripts

Handling sensitive data securely is of utmost importance in any development workflow. In this tech article, we will explore how to safely mask sensitive data in a shell script and integrate it with Terraform using the data source external. Specifically, we'll demonstrate how to echo the result with asterisks while retrieving an access token from Azure Active Directory, ensuring the sensitive information remains protected.

Understanding the Scenario
To demonstrate the masking technique and Terraform integration, we'll use a shell script (getazuretoken.sh) that retrieves an access token from Azure Active Directory. The script accepts two arguments, the Azure client ID and secret, and performs the necessary computations to obtain the access token.

Masking the Result
To echo the result with asterisks instead of the actual value, we can modify the script to include a masking mechanism. This ensures that the sensitive data is obfuscated when printed. Here's an example of the modified script:

#!/bin/bash
# getazuretoken.sh

# Retrieve the arguments passed from Terraform
arg1="$1"
arg2="$2"

# Perform some computations or retrieve data using the arguments

result=$(curl -X POST -d 'grant_type=client_credentials&client_id='${arg1}'&client_secret='${arg2}'&resource=https%3A%2F%2Fgraph.microsoft.com%2F' https://login.microsoftonline.com/TenantID/oauth2/token | sed -n 's/.*"access_token":"\([^"]*\)".*/\1/p')

# Mask the sensitive result
masked_result=$(printf '*%.0s' $(seq 1 ${#result}))

# Output JSON response with masked result
echo "{\"data\": \"$masked_result\"}"

Integrating with Terraform using data source external
Now, let's see how we can integrate this shell script with Terraform using the data source external. We'll define a new data source block in the Terraform configuration to execute the shell script and capture the masked result as an output. Here's an example:

data "external" "getazuretoken" {
  program = ["bash", "/path/to/getazuretoken.sh", var.azure_client_id, var.azure_client_secret]
}

output "masked_token" {
  value     = data.external.getazuretoken.result
  sensitive = true
}

In the above example, we define a data block with the external data source type. The program attribute specifies the shell script and passes the necessary variables from the Terraform configuration. We capture the result as an output named "masked_token". By setting sensitive = true, we ensure that the output value is masked in the Terraform console, logs, and outputs.

Implementation and Usage
To use this integration, make sure the shell script (getazuretoken.sh) and the Terraform configuration are in the same directory. Replace "/path/to/getazuretoken.sh" in the Terraform configuration with the actual path to the shell script. Provide the Azure client ID and secret as variables (var.azure_client_id and var.azure_client_secret) in your Terraform configuration.

Running terraform apply will execute the shell script, capture the masked result as an output, and display it in the Terraform output.

Security Considerations
While this approach effectively masks sensitive data in the Terraform output, it is essential to reinforce security best practices. This includes securely storing and managing the Azure client ID and secret, controlling access to the Terraform configuration, and considering additional security measures such as encryption and secure key management systems.

Conclusion:
Incorporating the masking technique in shell scripts allows for the secure handling of sensitive data in a Terraform workflow. By integrating the shell script using the data source external in Terraform, we can conveniently execute the script and capture the masked result as an output. This ensures that sensitive information, such as access tokens, remains protected throughout the Terraform execution and output.

By following the steps outlined in this article, you can enhance the security of your Terraform deployments, maintain compliance with data protection requirements, and contribute to a more robust and secure infrastructure provisioning process.