GSP106

The Data Loss Prevention API (DLP API) is a cloud-based service that helps you identify, classify, and protect sensitive data in the Google Cloud Platform. The DLP API can be used to scan for sensitive data in a variety of data sources, including Cloud Storage, BigQuery, and Cloud SQL.

The DLP API can be used to classify sensitive data in a variety of ways, including:

• Data types: such as PII, financial information, healthcare information, intellectual property, or regulatory data.
• Sensitivity levels: low, medium, or high.
• Categories: such as customer data, employee data, or financial data.

In this lab you will set up the Data Loss Prevention API and and use the API to inspect a string of data for sensitive information.

Setup and requirements

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.

This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

• Access to a standard internet browser (Chrome browser recommended).

Note: Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.

• Time to complete the lab---remember, once you start, you cannot pause a lab.

Note: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your account.

How to start your lab and sign in to the Google Cloud Console

1. Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:

   • The Open Google Console button
   • Time remaining
   • The temporary credentials that you must use for this lab
   • Other information, if needed, to step through this lab

2. Click Open Google Console. The lab spins up resources, and then opens another tab that shows the Sign in page.

   Tip: Arrange the tabs in separate windows, side-by-side.

   Note: If you see the Choose an account dialog, click Use Another Account.

3. If necessary, copy the Username from the Lab Details panel and paste it into the Sign in dialog. Click Next.

4. Copy the Password from the Lab Details panel and paste it into the Welcome dialog. Click Next.

   Important: You must use the credentials from the left panel. Do not use your Google Cloud Skills Boost credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

5. Click through the subsequent pages:

   • Accept the terms and conditions.
   • Do not add recovery options or two-factor authentication (because this is a temporary account).
   • Do not sign up for free trials.

After a few moments, the Cloud Console opens in this tab.

Note: You can view the menu with a list of Google Cloud Products and Services by clicking the Navigation menu at the top-left.

Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

1. Click Activate Cloud Shell at the top of the Google Cloud console.

When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. The output contains a line that declares the PROJECT_ID for this session:

Your Cloud Platform project in this session is set to YOUR_PROJECT_ID

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

2. (Optional) You can list the active account name with this command:

gcloud auth list

3. Click Authorize.

4. Your output should now look like this:

Output:

ACTIVE: * ACCOUNT: student-01-xxxxxxxxxxxx@qwiklabs.net To set the active account, run: $ gcloud config set account `ACCOUNT`

5. (Optional) You can list the project ID with this command:

gcloud config list project

Output:

[core] project = <project_ID>

Example output:

[core] project = qwiklabs-gcp-44776a13dea667a6 Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide. gcloud config set compute/region {{{project_0.default_region | ""}}}

Task 1. Download the DLP API

Download the DLP API files.

• Run the following command in Cloud Shell to clone the Node JS DLP repo:

git clone https://github.com/googleapis/nodejs-dlp.git

Task 2. Install dependencies

With the files downloaded and environment variable set, install the app's dependencies.

• Run the following commands:

npm install --save @google-cloud/dlp npm install yargs

You may see some warnings in the output, you can ignore them.

Task 3. Inspect a string for sensitive information

Now that the dependencies are installed, use the DLP API to inspect a string for sensitive information.

1. Run the following command to go into the nodejs-dlp/samples directory:

cd nodejs-dlp/samples

2. Run the following command to enable the DLP API:

gcloud services enable dlp.googleapis.com

3. Run the following command to inspect the string "My email address is joe@example.com." for sensitive information:

node inspectString.js {{{ project_0.project_id | "PROJECT_ID" }}} "My email address is joe@example.com." LIKELY 0 EMAIL_ADDRESS DICT_TYPE true Note: The usage for the inspectString.js file is as follows:

node inspectString.js my-project string minLikelihood maxFindings infoTypes customInfoTypes includeQuote

More info can be found in the Inspects strings section of this READ.ME documentation.

You should receive the following output:

Findings: Quote: joe@example.com Info type: EMAIL_ADDRESS Likelihood: LIKELY

The result shows what piece of sensitive data was found, what type of information it is, and how sure the API is that the string contains sensitive information.

Try running additional tests in your remaining lab time. You can find a list of dlp InfoTypes like PHONE_NUMBER and EMAIL_ADDRESS in the InfoType detector reference guide.

The following are a couple samples to get you started:

node inspectString.js {{{ project_0.project_id | "PROJECT_ID" }}} "My phone number is 555-555-5555" LIKELY 0 PHONE_NUMBER DICT_TYPE true node inspectString.js {{{ project_0.project_id | "PROJECT_ID" }}} "My phone# is 555-555-5555" LIKELY 0 PHONE_NUMBER DICT_TYPE true

Congratulations!

You have successfully identified and classified sensitive data.

Finish your quest

This self-paced lab is part of the Baseline: Deploy & Develop and Security & Identity Fundamentals quests. A quest is a series of related labs that form a learning path. Completing this quest earns you a badge to recognize your achievement. You can make your badge or badges public and link to them in your online resume or social media account. Enroll in a quest and get immediate completion credit. Refer to the Google Cloud Skills Boost catalog for all available quests.

Take your next lab

Continue your quest with the next lab in your quest, or check out these suggestions:

• Getting Started with Cloud KMS
• Cloud Functions: Qwik Start - Command Line

Next steps / Learn more

This lab is part of a series of labs called Qwik Starts. These labs are designed to give you a little taste of the many features available with Google Cloud. Search for "Qwik Starts" in the lab catalog to find the next lab you'd like to take!

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Manual Last Updated April 11, 2023

Lab Last Tested April 10, 2023

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