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Secrets Management

Secrets Management refers to the way in which we protect configuration settings and other sensitive data which, if made public, would allow unauthorized access to resources. Examples of secrets are usernames, passwords, api keys, SAS tokens etc.

We should assume any repo we work on may go public at any time and protect our secrets, even if the repo is initially private.

General Approach

The general approach is to keep secrets in separate configuration files that are not checked in to the repo. Add the files to the .gitignore to prevent that they're checked in.

Each developer maintains their own local version of the file or, if required, circulate them via private channels e.g. a Teams chat.

In a production system, assuming Azure, create the secrets in the environment of the running process. We can do this by manually editing the 'Applications Settings' section of the resource, but a script using the Azure CLI to do the same is a useful time-saving utility. See az webapp config appsettings for more details.

It's best practice to maintain separate secrets configurations for each environment that you run. e.g. dev, test, prod, local etc

The secrets-per-branch recipe describes a simple way to manage separate secrets configurations for each environment.

Note: even if the secret was only pushed to a feature branch and never merged, it's still a part of the git history. Follow these instructions to remove any sensitive data and/or regenerate any keys and other sensitive information added to the repo. If a key or secret made it into the code base, rotate the key/secret so that it's no longer active

Keeping Secrets Secret

The care taken to protect our secrets applies both to how we get and store them, but also to how we use them.

  • Don't log secrets
  • Don't put them in reporting
  • Don't send them to other applications, as part of URLs, forms, or in any other way other than to make a request to the service that requires that secret

Enhanced-Security Applications

The techniques outlined below provide good security and a common pattern for a wide range of languages. They rely on the fact that Azure keeps application settings (the environment) encrypted until your app runs.

They do not prevent secrets from existing in plaintext in memory at runtime. In particular, for garbage collected languages those values may exist for longer than the lifetime of the variable, and may be visible when debugging a memory dump of the process.

If you are working on an application with enhanced security requirements you should consider using additional techniques to maintain encryption on secrets throughout the application lifetime.

Always rotate encryption keys on a regular basis.

Techniques for Secrets Management

These techniques make the loading of secrets transparent to the developer.

C#/.NET

Use the file attribute of the appSettings element to load secrets from a local file.

<?xml version="1.0" encoding="utf-8"?>
<configuration>
  <appSettings file="..\..\secrets.config"></appSettings>
  <startup>
      <supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.6.1" />
  </startup></configuration>

Access secrets:

static void Main(string[] args)
{
    String mySecret = System.Configuration.ConfigurationManager.AppSettings["mySecret"];
}

When running in Azure, ConfigurationManager will load these settings from the process environment. We don't need to upload secrets files to the server or change any code.

Node

Store secrets in environment variables or in a .env file

$ cat .env
MY_SECRET=mySecret

Use the dotenv package to load and access environment variables

require('dotenv').config()
let mySecret = process.env("MY_SECRET")

Python

Store secrets in environment variables or in a .env file

$ cat .env
MY_SECRET=mySecret

Use the dotenv package to load and access environment variables

import os
from dotenv import load_dotenv


load_dotenv()
my_secret = os.getenv('MY_SECRET')

Another good library for reading environment variables is environs

from environs import Env


env = Env()
env.read_env()
my_secret = os.environ["MY_SECRET"]

Databricks

Databricks has the option of using dbutils as a secure way to retrieve credentials and not reveal them within the notebooks running on Databricks

The following steps lay out a clear pathway to creating new secrets and then utilizing them within a notebook on Databricks:

  1. Install and configure the Databricks CLI on your local machine
  2. Get the Databricks personal access token
  3. Create a scope for the secrets
  4. Create secrets

Validation

Automated credential scanning can be performed on the code regardless of the programming language. Read more about it here


Last update: May 12, 2021