Access Policies

AccessPolicy is an Aidbox custom resource representing a set of checks for the request. AccessPolicy resources are used to check request objects against a set of rules. If there are no AccessPolicy resources defined in Aidbox, all requests will be denied.

If AccessPolicies exist, Aidbox iterates through them, evaluating each AccessPolicy against the request object. As soon as one of them passes the validation (the evaluation result is true), the request is considered authorized, and Aidbox stops further policy evaluation. If all policies fail to validate it (all of them evaluated to false), then Aidbox denies the request and responds with 403 Forbidden.

The structure of the AccessPolicy resource and the request object are described below.

AccessPolicy resource structure

AccessPolicy resource has the following structure:

resourceType: AccessPolicy
description: policy description text

# type of evaluation engine
engine: allow | matcho| sql | json-schema | complex | allow-rpc | matcho-rpc

# engine-specific fields
# e.g. `schema` for `json-schema` engine
schema: {}

# References to either Client, User, or Operation resources
link:
- { resourceType: Operation, id: op-id }
- { resourceType: User, id: user-1 }
- { resourceType: Client, id: client-1 }

It supports various evaluation engines: Allow, JSON Schema, SQL, Matcho, and Complex, as well as Allow-RPC and Matcho-RPC. They specify how checks are implemented — with an SQL statement, with a JSON Schema, or as a list of allowed endpoints.

Request object structure

Aidbox evaluates AccessPolicy against a request object that represents an incoming HTTP request. It has the following structure:

# Request method (get/post/put/delete)
request-method: get

# Request scheme (http or https)
scheme: http

# Request URI (no query string)
uri: /fhir/Patient

# Query string
query-string: name=John

# Parsed query-string params merged with URL params extracted by the routing engine
params: {name: John, type: Patient}

# Request body (for POST, PUT or PATCH)
body: null

# Parsed JWT claims (if any)
jwt: {sub: xxxxxxx, jti: xxxxxxx, iss: aidbox, iat: 15409xxxxx, exp: 15409xxxxxa}

# Object containing current User resource (if any)
user:
  data:
    patient_id: 42
  email: [e-mail]
  id: b66bc7c5-1a56-422f-8cf8-e64469135ce2
  phone: [phone]
  resourceType: User
  # ...

# Client’s IP address
remote-addr: 10.128.0.6

# Client resource (if any)
client:
  id: b4930671-410c-462b-8b12-23cdef91af0c
  resourceType: Client
  # ...

# Request headers
headers: {x-original-uri: '/fhir/Patient?name=John' ...}

AccessPolicy links

AccessPolicy instance can be linked to User, Client or Operation resources with the AccessPolicy.link field. If AccessPolicy has no links, it’s considered a global policy. To authorize a request, Aidbox uses global policies in addition to all AccessPolicy rules linked to User, Client, and Operation associated with the current request.

Performance consideration. Link your policy to User, Client or Operation. Otherwise, it will be evaluated for every request, increasing the number of checks.

See tutorials:

AccessPolicy best practices

Debug Access Control

Evaluation engines

Aidbox provides several ways to specify rules for AccessPolicy resources — so-called evaluation engines. They come with their syntax and offer varying degrees of flexibility and convenience for writing those rules.

There are five evaluation engines:

Engine	Description	Use Cases
Allow	Simplest engine that allows everything for certain User, Client or makes Operation public	- Testing and development environments - Superuser/admin access - Public endpoints
Matcho	Mathes request context with a set of rules	- Most common access control scenarios (90% of cases)
JSON Schema	Uses JSON Schema validation for request objects	- For those familiar with JSON Schema
SQL	Uses SQL queries for access control logic	- Complex data-dependent rules - When you need to join multiple tables - Performance-critical scenarios
Complex	Combines multiple engines and conditions	- Multi-step validation workflows - When you need to combine different types of checks - Advanced access control scenarios

It is recommended to pick the Matcho engine. In 90% of cases, it is enough. Sometimes, the complex access policy can only be written by SQL or Complex engines.

Allow engine

The Allow engine is the simplest. It allows all requests.

The allow engine always evaluates true regardless of the request object. Use it if you want to provide unrestricted access to everything.

Example:

resourceType: AccessPolicy
id: this-policy-allows-everything
engine: allow
link:
- { resourceType: User, id: admin }

Matcho engine

Matcho engine leverages Matcho pattern matching, it has compact and declarative syntax with limited expressivity. It is well-suited for writing all sorts of rules and thus is one of the easiest options to specify AccessPolicy checks.

To test the Matcho engine without creating AccessPolicy and sending a request, you can use the $matcho endpoint.

Example

In this example, the request is allowed only if:

• Uri is related to Encounter. E.g. /fhir/Encounter or /Encounter,

• HTTP request is either GET or POST, not PUT,

• practitioner parameter provided as a query string in case of the GET request or body params in case of the POST request must be equal to practitioner_id of the user,

User data, which is fetched from the "user" table, must contain the inpatient department and practitioner.

resourceType: AccessPolicy
id: as-practitioner-who-works-in-inpatient-department-allowed-to-see-his-patients
engine: matcho
matcho:
  user: 
    department: inpatient
    # user.data.practitioner_id should be present
    data: 
      practitioner_id: present?
  # uri must match regexp /Encounter.*
  uri: '#/Encounter.*'
  request-method: {$enum: ['get', 'post']}
  params:
    practitioner: .user.data.practitioner_id 

SQL engine

The sql engine executes an SQL statement and uses its return value as an evaluation result. Thus, the statement should return a single row with just one column:

SELECT true FROM patient WHERE id = {{jwt.patient_id}} LIMIT 1;

SQL statement can refer to request fields with a double curly braces interpolation. The string inside the braces will be used as a path to value in the request object.

The SQL engine is sometimes the only way to perform complex checks when the AccesPolicy needs to check data stored in the database but not in the request context.

Example

Suppose that we are checking a request that comes with a User resource referencing a Practitioner through User.data.practitioner_id element. The following policy allows requests only to /fhir/Patient/<patient_id> URLs and only to those patients who have a Patient.generalPractitioner element referencing the same practitioner as a User of our current request. In other words, User as a Practitioner is only allowed to see his own patients — those who reference him as their generalPractitioner.

resourceType: AccessPolicy
id: practitioner-only-allowed-to-see-his-patients
engine: sql
sql:
  query: |
    SELECT
      {{user}} IS NOT NULL
      AND {{user.data.practitioner_id}} IS NOT NULL
      AND {{uri}} LIKE '/fhir/Patient/%'
      AND resource->'generalPractitioner' @>
    jsonb_build_array(jsonb_build_object('resourceType',
        'Practitioner', 'id', {{user.data.practitioner_id}}::text))
      FROM patient WHERE id = {{params.resource/id}};

Interpolation Rules

You can parameterize your SQL queries with request object using {{path}} syntax. For example, to get a user role provided {user: {data: {role: "admin"}}} you write {{user.data.role}}. Parameter expressions are escaped by default to protect from SQL injection.

For dynamic queries — to parameterize table name, for example — you have to use {{!path}} syntax. The expression SELECT true from {{!params.resource/type}} limit 1 when a request contains {params: {"resource/type": "Patient"}} will be transformed into SELECT true from "patient". By default, identifier names are double-quoted and lower-cased.

More examples

In this example, User as a Practitioner is only allowed to see the conditions of his patients — those who reference him as their generalPractitioner.

PUT /AccessPolicy/practitioner-only-allowed-to-see-his-patients-conditions

resourceType: AccessPolicy
id: practitioner-only-allowed-to-see-his-patients-conditions
engine: sql
sql:
  query: |
    SELECT 1
    FROM condition c
    JOIN patient p ON (
      c.resource @> (
        $JSON${
          "subject":{
            "id":"$JSON$
            ||
            p.id
            ||
            $JSON$",
            "resourceType":"Patient"
          }
        }$JSON$
      )::jsonb
    )
    WHERE
      {{user}} IS NOT NULL
      AND ({{user.data.practitioner_id}})::text IS NOT NULL
      AND ({{uri}})::text LIKE '/fhir/Condition/%'
      AND p.resource @> (
        $JSON${
          "generalPractitioner":[{
            "id":"$JSON$
            ||
            ({{user.data.practitioner_id}})::text
            ||
            $JSON$",
            "resourceType":"Practitioner"
          }]
        }$JSON$
      )::jsonb
      AND c.id = {{params.resource/id}}

JSON Schema

json-schema engine allows you to use JSON Schema to validate the request object. It is specified under schema a field of AccessPolicy resource. The currently supported JSON Schema version is draft-07.

Fields with empty values — [], {}, "", null — are removed from the request before access policy checks are applied. Make sure to specify all necessary fields as required.

It is recommended to use Matcho engine instead of JSON Schema engine. Matcho engine is more expressive due to its special keys.

Example

The following policy requires request.params.resource/type to be present and have a value of "Organization":

resourceType: AccessPolicy
engine: json-schema
schema:
  properties:
    params:
      required: [resource/type]
    properties:
      resource/type:
        const:
          Organization

Complex

The complex engine allows you to combine several rules with and and or operators. You can use any engine rule to define a rule and even complex engine itself but it is forbidden to have both and and or keys on the same level. Rules are defined as an array of objects that must include an engine with a set of corresponding keys.

How AND & OR work

Aidbox applies inner policies one after the other top-bottom.

AND rule

Aidbox applies policies till one of two events happens:

1. One policy rejects the access. No further policies are applied. The access is rejected

2. There are no more policies to evaluate. It means the access is granted

OR rule

Aidbox applies policies till at least one grants access. If it has happened no further policies are applied.

Example 1

resourceType: AccessPolicy
engine: complex
and:
  - { engine: "sql", sql: { query: "select true" } }       # check-1
  - engine: complex
    or:
      - { engine: "sql", sql: { query: "select false" } }  # check-2
      - { engine: "sql", sql: { query: "select false" } }  # check-3

Policy in the example above represents the following logical expression: check-1 AND (check-2 OR check-3)

Example 2

Let's split the SQL policy example from above into two separate rules and combine them under and rule:

resourceType: AccessPolicy
engine: complex
and:
  # Rule: request.user && request.user.data.practitioner_id are required
  - engine: json-schema
    schema:
      type: object
      required: ["user"]
      properties:
        user:
          type: object
          required: ["data"]
          properties:
            data:
              type: object
              required: ["practitioner_id"]
  # Rule: current practitioner is patient’s generalPractitioner
  - engine: sql
    sql:
      query: |
        SELECT
          {{uri}} LIKE '/fhir/Patient/%'
          AND resource->'generalPractitioner' @>
        jsonb_build_array(jsonb_build_object('resourceType',
            'Practitioner', 'id', {{user.data.practitioner_id}}::text))
          FROM patient WHERE id = {{params.resource/id}};

See also

• AccessPolicy resource schema
• AccessPolicy best practices
• Debug access control