GraphQL AuthZ - GraphQL Authorization layer

Today we are excited to introduce GraphQL AuthZ - a new open-source library for adding authorization layers in different GraphQL architectures.


GraphQL AuthZ is a flexible modern way of adding an authorization layer on top of your existing GraphQL microservices or monolith backend systems.

It plays well with both code-first and schema-first (SDL) development, supports different ways of attaching authorization rules, has zero dependencies in the core package (aside from a peer dependency on graphql-js), and keeps the schema clean from any authorization logic!

Also, GraphQL AuthZ has integration examples for all major GraphQL frameworks and libraries. Let’s dig a little deeper and break down the core features and how they can help you improve your GraphQL developer experience.

How Does It Work?

GraphQL AuthZ wraps the graphql.js execution phase and runs logic for enforcing defined authorization rules before and after this phase. The key function from graphql-js that is responsible for running the execution logic is named execute.

This simplified pseudo-code describes how the GraphQL AuthZ hooks into the process by wrapping the execute function.

import { execute as originalExecute } from 'graphql'
function execute(args) {
  const preExecutionErrors = runPreExecutionRules(args)
  if (preExecutionErrors) {
    return preExecutionErrors
  const result = originalExecute(args)
  const postExecutionErrors = runPostExecutionRules(args, result)
  if (postExecutionErrors) {
    return postExecutionErrors
  return result

By wrapping existing functionality we gain the following key benefits.

  • Compatibility with modern GraphQL technologies providing ways to wrap the graphql.js execute function. Here are a few working examples for Envelop, GraphQL Helix, Apollo Server, and express-graphql.
  • The executable GraphQL schema does not contain any authorization logic allowing more flexible re-usage for other use-cases
  • Authorization rules can be added on top of an existing remote GraphQL schema. GraphQL AuthZ can be added as a layer on your GraphQL gateway that composes smaller subgraphs into one big graph.
  • Separation of the authorization logic into two phases
    • The pre-execution phase for static authorization rules based on the context and incoming operation
    • The post-execution phase for flexible authorization rules based on the execution result

Failing Early in the Pre-Execution Phase

With GraphQL AuthZ it’s possible to execute authorization logic before any of the resolvers have been executed. This empowers you to fail the request in the early stage, send back an error and reduce server workload.

This technique works the best for authorization logic that is not dependent on remote data sources. For example, checking if the user is authenticated or has some certain role or permission.

// creating pre-execution rules
const IsAuthenticated = preExecRule()(context => !!context.user)
const IsEditor = preExecRule()(context => context.roles.has('editor'))

However, if you need the flexibility for fetching data from a remote source such as a database before you can determine whether an operation should be executed, you still have the power to leverage those data sources with async code.

This technique is a perfect fit for mutation fields, as you want to avoid executing the mutation operation if the user has insufficient permissions e.g. he does not own a specific resource.

// user can only publish a post if he owns it
const CanPublishPost = preExecRule()(async (context, fieldArgs) => {
  const post = await db.posts.get(fieldArgs.postId)
  return post.authorId === context.user?.id

Using the GraphQL Schema as a Data Source

By pursuing the GraphQL AuthZ approach your executable schema does not contain any authorization logic. This simplifies using the executable schema as a data source. For example, instead of calling a remote database using an interface attached to our context object directly, the graphql function from graphql.js package could be called, with the executable schema as an argument along with graphql operation. By doing this, the authorization layer is not dependent on the underlying database(s), its architecture, and ORM(s). It is dependent only on the GraphQL schema which is a dependency of the GraphQL authorization layer by design.

// using schema as a data source inside pre-execution rule
const CanPublishPost = preExecRule()(async (context, fieldArgs) => {
  const graphQLResult = await graphql({
    schema: context.schema,
    source: `query post($postId: ID!) { post(id: $postId) { author { id } } }`,
    variableValues: { postId: fieldArgs.postId }
  const post =
  return post && === context.user?.id

Authorization logic could require any kind of data fetched from different databases or (micro)services. Some data points could even be resolved by third-party microservices or APIs that are not part of the composed graph.

By using the GraphQL schema as the data source, authorization rules don’t need to be aware of complex implementation details or directly connect to different databases or microservices.

This makes GraphQL AuthZ extremely powerful, especially for subgraphs in a microservice architecture with centralized gateway-level authorization.

All the subschemas could live without any authorization logic and a federated or stitched gateway can leverage GraphQL AuthZ for actually applying global authorization logic for the whole graph while leveraging the graph for fetching the data required for doing so, without having to be aware of GraphQL resolver implementation details.

Reduce Remote Procedure Calls with Post-Execution Rules

In addition to the pre-execution rules, GraphQL AuthZ also allows you to write post-execution rules.

Fetching remote data from within authorization rules is powerful but it adds overhead and requires additional network roundtrips. In most cases, the data required for performing authorization logic is closely related to entities fetched via the GraphQL operation selection set. You can avoid this by performing authorization logic based on the execution result in the post-execution phase.

In your post-execution rules, you can specify a selection set for fetching additional data, related to the rule target, that is required for running the rule.

For example, if your rule is attached to some object field it could require additional information about sibling fields with their relations.

// creating post-execution rule
const CanReadPost = postExecRule({
  selectionSet: '{ status author { id } }'
  (context, fieldArgs, post, parent) =>
    post.status === 'public' || === context.user?.id

By using this technique we reduce remote procedure calls to individual data sources by executing authorization logic on top of GraphQL execution result that is enriched with the additional data specified by the authorization rules. Since related data is often stored in the same place it can be fetched from a data source in one roundtrip (via the GraphQL schema) instead of performing one remote procedure call for the authorization and one call for the actual data populating.


With GraphQL AuthZ it is possible to implement a centralized gateway authorization layer as well as microservice level authorization. You can choose between storing the whole authorization schema in a holistic way on a stitched or federated gateway or having dedicated authorization schemas for each subgraph/schema specified by your services. It is even possible to mix both approaches!

“Shifting this configuration out of the gateway makes subschemas autonomous, and allows them to push their own configuration up to the gateway—enabling more sophisticated schema releases.” — schema stitching handbook

The @graphql-authz/directive package provides a GraphQL directive that can be used to annotate types and fields within your subschemas SDL and a configuration transformer that can be used on the gateway to convert the subschema directives into explicit authorization settings.

# using @authz directive
type User {
  id: ID!
  email: String! @authz(rules: [IsAdmin])
  posts: [Post!]!
type Post @authz(rules: [CanReadPost]) {
  id: ID!
  title: String!
  body: String!
  status: Status!
  author: User!
type Query {
  users: [User!]! @authz(rules: [IsAuthenticated])
  post(id: ID!): Post
type Mutation {
  publishPost(postId: ID!): Post! @authz(rules: [CanPublishPost])

On top of that directives can as well be used in monolith architecture.

If you are not pursuing a schema-first (SDL) development flow and are more a fan of the code-first approach (which does not let you specify directives without framework-specific voodoo magic), the authorization schema can also be described as a plain JSON object. Allowing you to specify the rules that should be executed on your object types, interfaces, and fields.

// defining auth schema
const authSchema = {
  Post: { __authz: { rules: ['CanReadPost'] } },
  User: {
    email: { __authz: { rules: ['IsAdmin'] } }
  Mutation: {
    publishPost: { __authz: { rules: ['CanPublishPost'] } }
  Query: {
    users: { __authz: { rules: ['IsAuthenticated'] } }
  // wildcards are supported. read more:
  '*': {
    __authz: { rules: ['Reject'] },
    '*': {
      __authz: { rules: ['IsAuthenticated'] }

Comparing GraphQL AuthZ with GraphQL Shield

GraphQL Shield is a great tool for creating authorization layers that has vast adoption from the community. In fact, GraphQL AuthZ is highly inspired by GraphQL Shield! However, GraphQL Shield uses a different approach compared to GraphQL AuthZ for applying authorization rules.

The main difference is GraphQL Shield uses field middleware by wrapping all the resolver functions within your GraphQL schema for executing authorization logic during the data-resolving phase, while GraphQL AuthZ wraps the entire execute logic.

The benefits of the wrapping approach are described in previous paragraphs, however, there are also some drawbacks. For example, with GraphQL AuthZ post-execution rules there is no ability to fail the request early because post-execution rules are executed after all resolvers are executed. GraphQL Shield, on the other hand, can fail the request during the execution phase which happens before the post-execution phase but later than the pre-execution phase. On the other hand, post-execution rules have the benefit of accessing the resolved value of the field they are specified on and, furthermore, even the sibling fields that are specified via the rules selection set.

The middleware approach of GraphQL shield is missing these possibilities because authorization logic is executed in the context of field resolvers and has access only to the parent object which is the value returned from the parent field resolver. At that stage, the wrapped field resolvers have not been executed yet.

Another feature in GraphQL Shield is the built-in contextual caching mechanism for rules. At the moment, GraphQL AuthZ has no built-in caching, but you can implement it yourself within the GraphQL AuthZ rules, or in the future caching could even become a built-in feature. (pull requests are more than welcome)

Which Approach to Choose?

Let’s wrap up all the use-cases mentioned above and also give a library recommendation.

  • If you have very few places that should be covered by authorization, and you don’t plan to increase such places, you can just add authorization logic right inside resolvers to not overcomplicate things.
  • If all of your authorization logic doesn’t depend on the data and shouldn’t perform complex calculations, you can use operation-field-permissions Envelop plugin.
  • If your authorization logic contains some calculations which are the same for many fields of your schema, you can use GraphQL Shield to leverage the built-in contextual caching mechanism.
  • If your authorization logic heavily depends on the data, or you want to use schema directives to attach auth rules, you can use GraphQL AuthZ to leverage the ‘GraphQL schema as a data source’ pattern and post-execution rules.


GraphQL AuthZ is a new approach for applying GraphQL native authorization. We are happy that we can finally share this library with the community and keen to learn about the ways it might be used within your next project! Don’t hesitate to contact us for questions or to evaluate whether this library might be a fit for your architecture.

Please check out the GraphQL AuthZ repository on GitHub for learning more. You can find a tutorial on how to set it up in different ways and with different technologies.

The repository also contains the following, ready to run, examples:

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