Bytebase is an open-source database DevSecOps solution for Developer, Security, DBA, and Platform Engineering teams. The GitLab for database DevSecOps. This tutorial guides you through setting up data classification and masking using Bytebase’s API. By the end of this tutorial, you will have accomplished the following:

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Prerequisites

  • Docker installed
  • Download the api-example repository, you’ll only need data-classification folder for this tutorial

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Overview

This demo app simulates the process of fetching data from databases connected to Bytebase and setting classification levels. By integrating global masking configurations, different classification levels will correspond to varying degrees of data masking.

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Workflow

  1. Run a Bytebase instance and add a service account user
  2. Import the classification
  3. Configure the data masking based on the classification level
  4. Configure the environment variables and run the demo app
  5. In the demo set the classification and see the data masking result

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Run a Bytebase instance and add a service account user

  1. Start Bytebase via Docker and register an account which will be granted Workspace Admin role. 
    docker run --rm --init \
  --name bytebase \
  --publish 8080:8080 --pull always \
  --volume ~/.bytebase/data:/var/opt/bytebase \
  bytebase/bytebase:3.8.1
    You’ll need an API service account user too:
  2. Go to IAM&Admin > Users&Groups, click +Add User.
  3. Choose Service Account as the Type, fill in the Email with api-sample@service.bytebase.com, choose Workspace DBA as Roles, and click Confirm.
  4. Copy the Service Key for later use.

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Import the classification

  1. Go to Data Access > Data Classification, click Upload classification.
  2. Upload the /public/classification.json file within the data-classification repository, you’ll see the classification is imported.

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Configure the data masking based on the classification level

There are two ways to configure the data masking based on the classification level - via UI and API:

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UI

  1. Go to Data Access > Data Masking, click Add.
  2. Give it a Condition Name, e.g. Partial masking for Level 1, click Add Condition.
  3. Here we only care about data on production environment, so we set the Environment ID equals prod.
  4. Add another condition with AND operator, and set the Classification Level in Level 1.
  5. Choose Masking Level as Partial and click Confirm.
  6. The same way, we can add another masking rule for Level 2 with Masking Level as Full. bb-data-masking

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API

  1. Find the data masking configuration file within the data-security repository.
  2. Generate the token for the service account user: 
        export bytebase_url=http://localhost:8080
    bytebase_account="api-sample@service.bytebase.com"
    bytebase_password="bbs_bxxxxxxxxxoUxfY"
    bytebase_token=$(curl -v ${bytebase_url}/v1/auth/login \
        --data-raw '{"email":"'${bytebase_account}'","password":"'${bytebase_password}'","web":true}' \ --compressed 2>&1 | grep token | grep -o 'access-token=[^;]*;' | grep -o '[^;]*' | sed 's/access-token=//g; s/;//g')

    echo $bytebase_token
  3. Import the data masking configuration: 
        curl --request PATCH "${bytebase_url}/v1/policies/masking_rule?allow_missing=true&update_mask=payload" \
    --header 'Authorization: Bearer '${bytebase_token} \
    --data @global-masking-rule.json
  4. Login to Bytebase console and go to Data Access > Data Masking, you’ll see the data masking is configured.

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Configure the environment variables and run the data-classification demo app

  1. Go to the data-classification folder of the api-example repository, and copy env-template.local file as .env.local. Replace the placeholders with yours. 
    
 NEXT_PUBLIC_BB_HOST=http://localhost:8080
 NEXT_PUBLIC_BB_SERVICE_ACCOUNT=api-sample@service.bytebase.com
 NEXT_PUBLIC_BB_SERVICE_KEY=bbs_xxxxxxxxxxxWUrDf
  2. Run pnpm i and pnpm run dev, you can run the demo app locally with localhost:3000.

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Set the classification and see the data masking result

  1. In the demo app, select a table, here we select salary, it’s possible to set the classification level for this table, but here we skip it.
  2. Choose classification 1-4 Health [Level 2] for the amount column and 1-1 Basic [Level 1] for the from_date column. demo-two-levels
  3. Go to Bytebase SQL Editor, double click the salary table, you’ll see the data is masked accordingly. bb-sql-editor

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Code explanation

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Fetch database schema and classification

  1. Bytebase provides the possibility to set classification on the table and column level. So the first step is to fetch the database schema.
  2. Use the API /v1/instances/${instance}/databases/${database}/metadata to fetch the database schema information. In this demo, the instance is hardcoded as test-sample-instance and the database is test-sample-database. 
    const instance = 'prod-sample-instance';
const database = 'hr_prod';

const response = await fetch(
  `${process.env.NEXT_PUBLIC_BB_HOST}/v1/instances/${instance}/databases/${database}/metadata`,
  {
    method: 'GET',
    headers: {
      'Content-Type': 'application/json',
      Authorization: 'Bearer ' + token,
    },
    cache: 'no-store',
  },
);
  3. The metadata response includes the database schema under schemas: 
        "schemas": [
        {
            "name": "public",
            "tables": [
                {
                    "name": "dept_emp",
                    "columns": [
                        {
                            "name": "emp_no",
                            "position": 1,
                            "hasDefault": false,
                            "onUpdate": "",
                            "nullable": false,
                            "type": "integer",
                            "characterSet": "",
                            "collation": "",
                            "comment": "",
                            "userComment": "",
                            "effectiveMaskingLevel": "MASKING_LEVEL_UNSPECIFIED",
                            "generation": null
                        },
                        {
                            "name": "dept_no",
                            "position": 2,
                            "hasDefault": false,
                            "onUpdate": "",
                            "nullable": false,
                            "type": "text",
                            "characterSet": "",
                            "collation": "",
                            "comment": "",
                            "userComment": "",
                            "effectiveMaskingLevel": "MASKING_LEVEL_UNSPECIFIED",
                            "generation": null
                        },
                        ...
                    ]
                }
                ...
            ]
        }
    ]
    Meanwhile, it also includes the classification information under schemaConfigs: 
    "schemaConfigs": [
        {
            "name": "public",
            "tableConfigs": [
                {
                    "name": "employee",
                    "columnConfigs": [
                        {
                            "name": "birth_date",
                            "semanticTypeId": "",
                            "labels": {},
                            "classificationId": "1-3"
                        },
                        {
                            "name": "emp_no",
                            "semanticTypeId": "",
                            "labels": {},
                            "classificationId": "1-1"
                        }
                    ],
                    "classificationId": "",
                    "updater": "",
                    "sourceBranch": "",
                    "updateTime": null
                }
            ],
            "functionConfigs": [],
            "procedureConfigs": [],
            "viewConfigs": []
        }
    ]
    ...

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Update the schema with classification

  1. To update the schema with classification, we need to use the API /v1/instances/${instance}/databases/${database}/metadata with PATCH method.
const response = await fetch(
  `${process.env.NEXT_PUBLIC_BB_HOST}/v1/instances/${instance}/databases/${database}/metadata`,
  {
    method: 'PATCH',
    headers: {
      'Content-Type': 'application/json',
      Authorization: 'Bearer ' + token,
    },
    body: JSON.stringify(req),
    cache: 'no-store',
  },
);

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Fetch defined classification

  1. Log in Bytebase, go to Data Access > Data Classification. Upload the classification.json file. It will be parsed and saved as global classification.
  2. Use the API /v1/settings/bb.workspace.data-classification to fetch the defined classification, so it’s always up to date.

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Summary

Setting up data classification and masking with Bytebase via API is a powerful way to manage sensitive data across your organization. This approach ensures that sensitive data is protected according to your organization’s security policies, while still allowing authorized users to access the data they need.