Introduction To Serverless Security: Part 3 - Preventing Accidental Deletion

Introduction To Serverless Security: Part 3 - Preventing Accidental Deletion

"Did I just delete the database with all my customer data?!" you might say if you failed to enable the measure to prevent accidental deletion. We will explore how to avoid this pitfall in your Serverless environment.

Serverless Make It Really Easy to Deploy Your Environment—and Undeploy Too

The Serverless framework has made it extremely easy to deploy you functions, create databases, provision storage, and more with one deploy command. This is powerful and convenient, but the same goes for tearing down your deployment. (You may want to read the first article in this series, "Introduction To Serverless Security: Part 1 - Dependencies," to get a quick overview on serverless environments.)

Deploying Your Environment

This example deployment file shows how you can configure the resources you want in one configuration.

service: secjuice-example

provider:
  name: aws
  runtime: nodejs8.10
  stage: ${opt:stage, 'dev'}
  region: us-east-1

functions:
  exampleFunction:
    handler: functions/example.handler
    events:
      - http:
          path: secjuice/example
          method: get


resources:
  Resources:
    S3BucketFiles:
      Type: AWS::S3::Bucket
      Properties:
          # must be globally unique across all AWS
        BucketName: secjuice-example-files
    CustomersTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: secjuice-example-customers
        AttributeDefinitions:
          - AttributeName: AccountId
            AttributeType: S
        KeySchema:
          - AttributeName: AccountId
            KeyType: HASH
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

The serverless.yml configuration file.

The serverless.yml configuration creates the following upon deployment to Amazon Web Services (AWS):

  • One function called secjuice-example-dev-exampleFunction using AWS Lambdas; it automatically appends the "service" and "stage" to the lambda function name

A Serverless deploy created the Lambda function.

  • One file storage system called secjuice-example-files using AWS Simple Storage Service (S3)

A Serverless deploy created the S3 buckets.

  • One database called secjuice-example-customers using AWS DynamoDB.

A Serverless deploy created the DynamoDB table.

To start the deploy, you navigate to the project folder where the serverless.yml file exists and run the following command:

sls deploy

Command to deploy the stack.

Wow! Deploying the stack is really simple.

Undeploying (i.e. Removing) Your Enviroment

As simple as it was to deploy, the same applies to removing your environment. This is a double-edge sword. You may want to remove your environment quickly when developing for multiple reasons, but you might not want that same ease with your production environment (and important data).

To start the removal, you navigate to the project folder where the serverless.yml file exists and run the following command:

sls remove

Command to remove the stack.

It is scary how easy it was to delete the entire stack.

Issuing this command deleted the following:

  • The DynamoDB database

A Serverless remove deleted the DynamoDB table.

  • The S3 bucket

A Serverless remove deleted the S3 buckets.

  • The Lambda function

A Serverless remove deleted the Lambda function.

How can you protect your data from an accidental (or maliciously intended) deletion?

Strategies to Protect Your Data From Accidental Deletion

Separating Function and Data Stacks

You can separate your functions and data into two stacks. I did accomplished this by creating two sub-folders "data" and "functions", each with its own serverless.yml configuration file.

service: secjuice-example-functions

provider:
  name: aws
  runtime: nodejs8.10
  stage: ${opt:stage, 'dev'}
  region: us-east-1

functions:
  exampleFunction:
    handler: example.handler
    events:
      - http:
          path: secjuice/example
          method: get

The functions/serverless.yml configuration file.

service: secjuice-example-data

provider:
  name: aws
  runtime: nodejs8.10
  stage: ${opt:stage, 'dev'}
  region: us-east-1

resources:
  Resources:
    S3BucketFiles:
      Type: AWS::S3::Bucket
      Properties:
          # must be globally unique across all AWS
        BucketName: secjuice-example-files
    CustomersTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: secjuice-example-customers
        AttributeDefinitions:
          - AttributeName: AccountId
            AttributeType: S
        KeySchema:
          - AttributeName: AccountId
            KeyType: HASH
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

The data/serverless.yml configuration file.

To start the deploy, you navigate to the project folder where the original serverless.yml file existed and run the following commands:

cd functions
sls deploy
cd ../data
sls deploy
cd ..

Commands to deploy both stacks.

These two deploys did the following:

  • Created two CloudFormation stacks

Each Serverless deploy created a stack.

  • Created the Lambda function

The Serverless deploy for the functions stack created the Lambda function.

  • Created the DynamoDB table

The Serverless deploy for the data stack created the DynamoDB table.

  • Created the S3 buckets

Each Serverless deploy created its S3 buckets.

Now, let's remove on the functions stack.

cd functions
sls remove
cd ..

Commands to remove the functions stack.

You will notice only the Lambda function and the S3 bucket associated with the functions stack is removed:

  • Only the data CloudFormation stack remains.

The Serverless remove for the functions stack removed its CloudFormation stack.

  • Only the data stack S3 buckets remain.

The Serverless remove for the functions stack removed its S3 bucket.

  • The DynamoDB table remains.

The Serverless remove for the functions stack had no effect on the DynamoDB table.

  • There is no Lambda function.

The Serverless remove for the functions stack removed the Lambda function.

This approach allows a developer to work on the Lambda functions without worrying about the effect it has to the data.

Enabling Termination Protection

AWS CloudFormation has a nice feature to protect against accidental termination: it is called "termination protection." Termination protection is disabled by default. To enable it:

  • Go to the stack
  • Click "Stack actions"
  • Click "Edit termination protection"

Navigating to the "Edit termination protection" option.

  • Click "Enabled"
  • Click "Save"

Enabling termination protection.

Now, when you try to remove the data stack you will get the following error:

Serverless: Getting all objects in S3 bucket...
Serverless: Removing objects in S3 bucket...
Serverless: Removing Stack...

  Serverless Error ---------------------------------------

  Stack [secjuice-example-data-dev] cannot be deleted while TerminationProtection is enabled

Error displayed when attempting to remove a stack with termination protection enabled.

Enabling termination protection via the web console is very simple, but can be time consuming if you have a lot of stacks to manage. I recommend enabling it as part of the Serverless deploy.

At the time of this writing, the Serverless framework version 1.x has no support for termination protection. You need to use a Serverless plugin to add that capability. You can use one of two plugins:

The "serverless-stack-termination-protection" plugin

This plugin enables termination protection during deploy without any additional configuration.

To install it, run the following commands in your project folder:

cd data
npm install --save-dev serverless-stack-termination-protection

Commands to install the plugin.

Open the serverless.yml configuration file for the data stack and add the plugin.

service: secjuice-example-data

provider:
  name: aws
  runtime: nodejs8.10
  stage: ${opt:stage, 'dev'}
  region: us-east-1

resources:
  Resources:
    S3BucketFiles:
      Type: AWS::S3::Bucket
      Properties:
          # must be globally unique across all AWS
        BucketName: secjuice-example-files
    CustomersTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: secjuice-example-customers
        AttributeDefinitions:
          - AttributeName: AccountId
            AttributeType: S
        KeySchema:
          - AttributeName: AccountId
            KeyType: HASH
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

plugins:
  - serverless-stack-termination-protection

The updated data/serverless.yml configuration file.

You will see the following output when you deploy the data stack:

serverless-stack-termination-protection:  Successfully enabled termination protection

Output displayed when deploying the data stack.

Disclosure: I wrote the "serverless-stack-termination-protection" plugin.

The "serverless-termination-protection" plugin

This plugin also enables termination protection during deploy, but offers additional configuration options to deploy to specific stages. For example, you can specify to enable termination protection only for your "prod" stage/environment.

To install it, run the following commands in your project folder:

cd data
npm install --save-dev serverless-termination-protection aws-sdk

Commands to install the plugin.

Open the serverless.yml configuration file for the data stack and add the plugin.

service: secjuice-example-data

provider:
  name: aws
  runtime: nodejs8.10
  stage: ${opt:stage, 'dev'}
  region: us-east-1

resources:
  Resources:
    S3BucketFiles:
      Type: AWS::S3::Bucket
      Properties:
          # must be globally unique across all AWS
        BucketName: secjuice-example-files
    CustomersTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: secjuice-example-customers
        AttributeDefinitions:
          - AttributeName: AccountId
            AttributeType: S
        KeySchema:
          - AttributeName: AccountId
            KeyType: HASH
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

plugins:
  - serverless-termination-protection

custom:
  serverlessTerminationProtection:
    stages:
      - prod

The updated data/serverless.yml configuration file.

You will see the following output when you deploy the data stack:

Serverless: STP: Adding termination protection to secjuice-example-data-dev..
Serverless: STP: Checking if termination protection should be added..
Serverless: STP: Stages to check: prod
Serverless: STP: Not applying termination protection for dev stage

Output displayed when deploying the data stack.

With either plugin, your data stack is now protected, unless you specify to exclude a stage.

Conclusion

Consider separating your stacks and enabling termination protection on the data stack at a minimum to protect your application from accidental deletion.

Before You Go

Source

The source files are available at https://github.com/miguel-a-calles-mba/secjuice/tree/master/termination-protection-examples for your enjoyment.

Before you go

About the author


Originally published on Secjuice.com

Photo by Blaine Lingard on Dribbble

Did you find this article valuable?

Support Miguel A. Calles MBA by becoming a sponsor. Any amount is appreciated!