Graphql Introspection in Actix with Dynamodb

GraphQL introspection allows clients to query the schema for types, queries, and mutations. In an Actix web service that uses DynamoDB as the backend data store, enabling introspection without access controls creates an information disclosure vector. An attacker can send an introspection query over an unauthenticated or weakly authenticated endpoint to discover the exact GraphQL operations and data shapes supported by the API. Because DynamoDB is often used with custom resolvers that map fields to specific table names and key schemas, the introspection response can reveal table names, key attribute names, and expected payload structures. This metadata helps an attacker craft more precise attacks such as BOLA/IDOR or injection attempts. The combination is risky when introspection is left available in production, especially if the Actix service also exposes unauthenticated GraphQL endpoints for public clients.

For example, a typical introspection query might look like this when sent to an Actix GraphQL endpoint:

query IntrospectionQuery {
  __schema {
    queryType {
      name
    }
    types {
      name
      kind
      fields {
        name
        args {
          name
          type {
            name
            kind
          }
        }
      }
    }
  }
}

If the Actix GraphQL server responds with full schema details, an attacker can see which DynamoDB-backed fields are available and infer access patterns. This can be combined with other checks such as BFLA or Property Authorization testing to identify endpoints where authorization is missing or misapplied. The presence of DynamoDB-specific field naming (e.g., PK/SK conventions) further exposes internal data modeling choices that should not be public. Since middleBrick tests include GraphQL introspection as part of its unauthenticated attack surface checks, it can flag whether introspection is too permissive and provide remediation guidance.

To reduce exposure, disable introspection for production builds in your Actix GraphQL server and enforce authentication where possible. When using DynamoDB, ensure that the GraphQL layer does not leak table or key schema details, and apply field-level authorization consistently. Below are concrete remediation steps and code examples for an Actix service using the async-graphql and rusoto_dynamodb crates.

1. Disable introspection in production builds by customizing the schema builder:

use async_graphql::{Schema, EmptySubscription, http::GraphiQLSource};
use async_graphql_actix_web::{GraphQLRequest, GraphQLResponse};
use actix_web::{web, App, HttpServer, HttpResponse};

struct Query;
#[Object]
impl Query {
    async fn public_data(&self) -> String {
        "safe data".to_string()
    }
}

let schema = Schema::build(Query, EmptySubscription::new()).disable_introspection().finish();

async fn graphql_handler(schema: web::Data<Schema<Query, EmptySubscription>>, req: GraphQLRequest) -> GraphQLResponse {
    let response = schema.execute(req.into_inner()).await;
    GraphQLResponse::from(response)
}

#[actix_web::main]
async fn main() -> std::io::Result<()> {
    HttpServer::new(move || {
        App::new()
            .app_data(web::Data::new(schema.clone()))
            .route("/graphql", web::post().to(graphql_handler))
    })
    .bind("127.0.0.1:8080")?
    .run()
    .await
}

The disable_introspection method ensures that introspection queries return an error in production, reducing schema leakage. This is important when the underlying resolvers query DynamoDB tables whose names and key schemas you do not want exposed.

2. Apply field-level authorization and avoid exposing DynamoDB metadata in error messages. Use a data loader pattern to batch DynamoDB requests and ensure that each resolver checks permissions against the authenticated user’s scope. Example using aws-sdk-dynamodb (v0.24+) with Actix:

use aws_sdk_dynamodb::Client;
use async_graphql::{Context, Object, Result};

struct Query {
    client: Client,
}

#[Object]
impl Query {
    async fn user_profile(&self, ctx: &Context<'_>, user_id: String) -> Result<String> {
        let actor_id = ctx.data_opt::()?;
        // Ensure the actor is allowed to view this user_id
        if actor_id != Some(user_id.clone()) {
            return Err("Unauthorized".into());
        }
        let table_name = "Users";
        let key = aws_sdk_dynamodb::model::AttributeValue::S(user_id);
        let output = self.client.get_item()
            .table_name(table_name)
            .key("PK", aws_sdk_dynamodb::model::AttributeValue::S("USER#".to_string() + &key.as_s().unwrap_or(&key).clone()))
            .send()
            .await
            .map_err(|e| async_graphql::Error::new(e.to_string()))?;
        if let Some(item) = output.item() {
            // map DynamoDB JSON to domain type
            return Ok(format!("{:?}", item));
        }
        Err("Not found".into())
    }
}

In this pattern, the resolver verifies that the requesting actor matches the requested user_id before constructing a DynamoDB key, preventing horizontal privilege escalation. Avoid returning raw DynamoDB error details to the client; map them to generic messages to prevent information leakage about table structures.

3. Use environment-based schema configuration so introspection and debug features are only available in staging or development. Combine this with middleware that logs suspicious introspection attempts for further analysis.