GraphQL Attack Surface
GraphQL Attack Surface
What Is an Attack Surface?
An attack surface refers to all potential entry points an attacker can exploit to compromise a system. GraphQL, like any system, has its own unique vulnerabilities based on its features and configuration. These entry points include queries, mutations, subscriptions, and various other elements of the GraphQL language and type system.
Imagine a building with multiple doors and windows. Each entry point is an opportunity for attackers to exploit vulnerabilities. Similarly, GraphQL’s extensive capabilities create opportunities for misconfigurations, improper validation, and exploitation.
Core Components of the GraphQL Language
1
Operation type
Type that defines the method of interaction with the server (query, mutation, or subscription)
2
Operation name
Arbitrary client-created label used to provide a unique name to an operation
3
Top-level field
Function that returns a single unit of information or object requested within an operation (may contain nested fields)
4
Argument (of a top-level field)
Parameter name used to send information to a field to tailor the behavior and results of that field
5
Value
Data related to an argument sent to a field
6
Field
Nested function that returns a single unit of information or object requested within an operation
7
Directive
Feature used to decorate fields to change their validation or executio
GraphQL queries consist of various components, each of which has security implications:
Operation Types:
Query: Retrieve data.
Mutation: Modify data, such as creating or updating records.
Subscription: Facilitate real-time communication between clients and servers.
Example: Mutation Query
mutation {
editPaste(id: 1, content: "My first mutation!") {
paste {
id
title
content
}
}
}
This mutation modifies the content of a specific paste while also fetching the updated data. The flexibility in mutation operations can be a source of business logic vulnerabilities.
Subscriptions: Subscriptions rely on WebSocket connections for real-time updates. While useful, they are prone to vulnerabilities such as Cross-Site WebSocket Hijacking (CSWSH) and Man-in-the-Middle (MITM) attacks if origin validation or encryption (via TLS) is absent.
Example: WebSocket Handshake Request:
GET /subscriptions HTTP/1.1
Host: 0.0.0.0:5013
Connection: Upgrade
Upgrade: websocket
Response:
HTTP/1.1 101 Switching Protocols
Upgrade: websocket
Connection: Upgrade
After the handshake, a subscription might look like this:
subscription {
paste {
id
title
content
}
}
Example: Query with Arguments
query {
users(id: 1) {
id
username
}
}
Key Attack Vectors in GraphQL
Field Suggestions: When a field is misspelled, GraphQL servers often suggest corrections. This helpful feature can inadvertently expose undocumented fields.
Example: Error Message with Suggestions
"Cannot query field \\"titl\\" on type \\"PasteObject\\". Did you mean \\"title\\"?"
Nested Queries: GraphQL allows deep nesting, which can lead to recursive queries and potential server overload.
Example: Circular Field Relationships
{
id
title
content
owner {
name
posts {
title
author {
name
}
}
}
}
Argument Exploitation: Arguments are client-driven and can contain malicious inputs. For example, improperly validated inputs can lead to injection attacks.
Example: Argument Exploitation
query {
users(id: "1; DROP TABLE users;") {
id
username
}
}
Aliases
Aliases allow renaming fields in GraphQL queries, resolving conflicts when the same field is queried with different arguments. For example:
Without aliases:
query {
pastes(public: false) {
title
}
pastes(public: true) {
title
}
}
Error: Fields conflict due to differing arguments.
With aliases:
query {
queryOne: pastes(public: false) {
title
}
queryTwo: pastes(public: true) {
title
}
}
Response:
{
"data": {
"queryOne": [{ "title": "My Title!" }],
"queryTwo": [{ "title": "Testing Testing" }]
}
}
Fragments
Fragments allow reusable field sets for improved readability:
fragment CommonFields on PasteObject {
title
content
}
query {
pastes {
...CommonFields
}
}
Security Implications
From a security perspective, fragments can be constructed such that they reference one another, which can create a circular fragment condition that could lead to denial-of-service (DoS) conditions
. This is because a circular dependency among fragments can lead to an infinite loop when the GraphQL server attempts to resolve the query
For example, consider a scenario with two fragments, Start and End:
query {
pastes {
...Start
}
}
fragment Start on PasteObject {
title
content
...End
}
fragment End on PasteObject {
...Start
}
In this case, the Start fragment includes the End fragment, which includes the Start fragment again, creating a circular reference. This can lead to a DoS condition if the server doesn't handle such circular references correctly
Variables
Variables in GraphQL are a way to pass dynamic values to a query, mutation, or subscription, making operations more flexible and reusable. They are defined using a dollar sign ($) symbol followed by a name and a type
query publicPastes($status: Boolean!) {
pastes(public: $status) {
id
title
content
}
}
In this example, $status is a variable of type Boolean that is passed to the public argument of the pastes field. The client would then provide the value for $status as a JSON object, such as {"status": true} or {"status": false}, along with the query
{
"status": false
}
Directives
Directives modify field behavior dynamically. Common directives:
@skip
Omits a field when the condition is true
Query
@include
Includes a field only when true
Query
@deprecated
Marks a field/type as deprecated
Schema
@specifiedBy
Specifies a scalar type via URL
Schema
Example:
query pasteDetails($pasteOnly: Boolean!) {
pastes {
id
title
content
owner @skip(if: $pasteOnly) {
name
}
}
}
Custom directives like @computed
can enhance functionality, e.g., merging fields:
type User {
firstName: String
lastName: String
fullName: String @computed(value: "$firstName $lastName")
}
Data Types
GraphQL supports six types: Object, Scalar, Enum, Union, Interface, and Input.
Objects
Custom types with specific fields:
type PasteObject {
id: ID!
title: String
content: String
public: Boolean
}
Scalars
Core scalar types include ID
, Int
, Float
, String
, Boolean
. Implementations can also define their own custom scalars.
scalar DateTime
type PasteObject {
id: ID!
title: String}
content: String
public: Boolean
userAgent: String
ipAddr: String
ownerId: Int
burn: Boolean
owner: OwnerObject
createdAt: DateTime!
}
Enums
Enums are special types that allow a field to return only one value from a predefined set of possible values. They are useful when you want to restrict a field to specific options.
Here's how they work:
You define an enum type by listing all possible values it can have. For example, the UserSortEnum allows sorting users by
ID
,EMAIL
,USERNAME
, orDATE_JOINED
When using an enum in a query, you can only use one of these predefined values. For instance, in the example query, users are being sorted by ID:
Allow specific values for fields:
enum UserSortEnum {
ID
EMAIL
USERNAME
DATE_JOINED
}
input UserOrderType {
sort: UserSortEnum!
}
type UserObject {
id: Int!
username: String!
}
type Query {
users(limit: Int, order: UserOrderType): UserObject!
}
Example Query:
query {
users(limit: 100, order: { sort: ID })
}
Unions
Return one of multiple object types:
union SearchResults = UserObject | PasteObject
type UserObject {
id: ID!
username: String!
}
type PasteObject {
id: ID!
title: String
content: String
--snip--
}
type Query {
search(keyword: String): [SearchResults!]
}
Query:
query {
search(keyword: "p") {
... on UserObject { username }
... on PasteObject { title content }
}
}
---------------
// result
{
"data": {
"search": [
{
"title": "This is my first paste",
"content": "What does your room look like?"
},
{
"id": "2",
"username": "operator"
}}
}
]
Interfaces
Define common fields across types:
interface SearchItem {
keywords: [String!]
}
type UserObject implements SearchItem {
id: ID!
username: String!
keywords: [String!]
}
type PasteObject implements SearchItem {
id: ID!
title: String
content: String
keywords: [String!]
--snip--
}
type Query {
search(keyword: String): [SearchItem!]!
}
Inputs
Simplify passing complex arguments:
input UserInput {
username: String!
password: String!
email: String!
}
Mutation example:
mutation newUser($input: UserInput!) {
createUser(userData: $input) {
user {
username
}
}
}
JSON for variables:
{
"input": {
"username": "tom",
"password": "secret",
"email": "tom@example.com"
}
}
Apologies for missing the source code earlier. Here's a revised version that includes all relevant queries and responses.
GraphQL Introspection
__Schema
Provides all information about the schema of a GraphQL service
__Type
Provides all information about a type
__TypeKind
Provides the different kinds of types (scalars, objects, interface, union, enum, and so on)
__Field
Provides all information for each field of an object or interface type
__InputValue
Provides field and directive argument information
__EnumValue
Provides one of the possible values of an enum
__Directive
Provides all information on both custom and built-in directives
Empowering Clients:
Introspection allows clients to discover schema information, including:
Queries
Mutations
Subscriptions
Types
Fields
Directives
Example query for listing all types:
query { __schema { types { name } } }
Response:
{ "data": { "__schema": { "types": [ { "name": "PasteObject" }, { "name": "ID" }, { "name": "String" }, { "name": "OwnerObject" }, { "name": "UserObject" } ] } } }
Deep Dive into Custom Types:
Investigate specific types to uncover fields and relationships:
query { __type(name: "PasteObject") { name kind fields { name type { name kind } } } }
Response:
{ "__type": { "name": "PasteObject", "kind": "OBJECT", "fields": [ { "name": "id", "type": { "name": null, "kind": "NON_NULL" } }, { "name": "title", "type": { "name": "String", "kind": "SCALAR" } }, { "name": "content", "type": { "name": "String", "kind": "SCALAR" } }, { "name": "owner", "type": { "name": "OwnerObject", "kind": "OBJECT" } } ] } }
Validation and Execution
Validation Process:
GraphQL queries are checked against the schema for:
Field existence
Argument correctness
Directive support
GraphQL Threat Matrix:

A framework for comparing GraphQL implementations based on:
Security maturity
Default configurations
Known vulnerabilities
Execution Stage:
Resolvers process valid queries, but weak implementations can lead to exploits.
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