Security context

Your authentication server issues JWTs to your client application, which, when sent as part of the request, are verified and decoded by Cube to get security context claims to evaluate access control rules. Inbound JWTs are decoded and verified using industry-standard JSON Web Key Sets (JWKS) (opens in a new tab).

For access control or authorization, Cube allows you to define granular access control rules for every cube in your data model. Cube uses both the request and security context claims in the JWT token to generate a SQL query, which includes row-level constraints from the access control rules.

JWTs sent to Cube should be passed in the Authorization: <JWT> header to authenticate requests.

JWTs can also be used to pass additional information about the user, known as a security context. A security context is a verified set of claims about the current user that the Cube server can use to ensure that users only have access to the data that they are authorized to access.

It will be accessible as the securityContext property inside:

The query_rewrite configuration option in your Cube configuration file.
the COMPILE_CONTEXT global, which is used to support multi-tenant deployments.

By convention, the contents of the security context should be an object (dictionary) with nested structure:

{
  "sub": "1234567890",
  "iat": 1516239022,
  "user_name": "John Doe",
  "user_id": 42,
  "location": {
    "city": "San Francisco",
    "state": "CA"
  }
}

Reserved elements

Some features of Cube Cloud (e.g., authentication integration and LDAP integration) use the cubeCloud element in the security context. This element is reserved and should not be used for other purposes.

Using query_rewrite

You can use query_rewrite to amend incoming queries with filters. For example, let's take the following query:

{
  "measures": [
    "orders_view.count"
  ],
  "dimensions": [
    "orders_view.status"
  ]
}

We'll also use the following as a JWT payload; user_id, sub and iat will be injected into the security context:

{
  "sub": "1234567890",
  "iat": 1516239022,
  "user_id": 42
}

Cube expects the context to be an object. If you don't provide an object as the JWT payload, you will receive the following error:

Cannot create proxy with a non-object as target or handler

To ensure that users making this query only receive their own orders, define query_rewrite in the configuration file:

Python

JavaScript

To test this, we can generate an API token as follows:

Python

JavaScript

Using this token, we authorize our request to the Cube API by passing it in the Authorization HTTP header.

curl \
  -H "Authorization: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1Ijp7ImlkIjo0Mn0sImlhdCI6MTU1NjAyNTM1MiwiZXhwIjoxNTU4NjE3MzUyfQ._8QBL6nip6SkIrFzZzGq2nSF8URhl5BSSSGZYp7IJZ4" \
  -G \
  --data-urlencode 'query={"measures":["orders.count"]}' \
  http://localhost:4000/cubejs-api/v1/load

And Cube will generate the following SQL:

SELECT
  "orders".STATUS "orders_view__status",
  count("orders".ID) "orders_view__count"
FROM
  ECOM.ORDERS AS "orders"
  LEFT JOIN ECOM.USERS AS "users" ON "orders".USER_ID = "users".ID
WHERE
  ("users".ID = 42)
GROUP BY
  1
ORDER BY
  2 DESC
LIMIT
  5000

Using COMPILE_CONTEXT

COMPILE_CONTEXT can be used to create fully dynamic data models. It enables you to create multiple versions of data model based on the incoming security context. The first thing you need to do is to define the mapping rule from a security context to the id of the compiled data model. It is done with context_to_app_id configuration option.

from cube import config
 
@config('context_to_app_id')
def context_to_app_id(ctx: dict) -> str:
  return ctx['securityContext']['team']

It is common to use some field from the incoming security context as an id for your data model. In our example, as illustrated below, we are using team property of the security context as a data model id.

Once you have this mapping, you can use COMPILE_CONTEXT inside your data model. In the example below we are passing it as a variable into masked helper function.

cubes:
  - name: users
    sql_table: ECOM.USERS
    public: false
 
    dimensions:
      - name: last_name
        sql: {{ masked('LAST_NAME', COMPILE_CONTEXT.securityContext) }}
        type: string

This masked helper function is defined in model/globals.py as follows: it checks if the current team is inside the list of trusted teams. If that's the case, it will render the SQL to get the value of the dimension; if not, it will return just the masked string.

from cube import TemplateContext
 
template = TemplateContext()
 
@template.function('masked')
def masked(sql, security_context):
  trusted_teams = ['cx', 'exec' ]
  is_trusted_team = security_context.setdefault('team') in trusted_teams
  if is_trusted_team:
    return sql
  else:
    return "'--- masked ---'"

Usage with pre-aggregations

To generate pre-aggregations that rely on COMPILE_CONTEXT, configure scheduledRefreshContexts in your cube.js configuration file.

Testing during development

During development, it is often useful to be able to edit the security context to test access control rules. The Developer Playground allows you to set your own JWTs, or you can build one from a JSON object.

Access control Member-level security