Broken Access Control in Actix with Firestore

Broken Access Control occurs when an API fails to properly enforce authorization between different users or roles, allowing one user to access or modify data belonging to another. In an Actix-web service that uses Google Cloud Firestore as the backend data store, this risk is amplified when authorization checks are missing, inconsistent, or incorrectly tied to the Firestore document identity rather than to the authenticated user.

Consider a typical REST pattern in Actix where a route like GET /users/{user_id} retrieves a user profile. If the handler looks up the document by user_id from the URL but does not verify that the authenticated principal owns or is permitted to view that document, an unauthenticated or low-privilege actor can enumerate IDs and read other users' data. This is a classic BOLA/IDOR pattern. Firestore security rules alone do not protect an API in this scenario because the request reaches your Actix service with a valid service identity (e.g., a service account or API key). Once the backend authenticates to Firestore, rules may permit broad read or write access, and it becomes the application's responsibility to enforce per-user authorization before issuing any Firestore read or write.

Middleware or client libraries that auto-map URL parameters to Firestore paths can unintentionally expose this gap. For example, if an endpoint accepts a document_id query parameter or path segment and directly uses it in a Firestore collection("orders").document(document_id).get() without ensuring the document belongs to the requesting user, an attacker can supply arbitrary IDs to access or modify data across tenants. This becomes a BFLA/Privilege Escalation vector when role or permission claims are not validated before constructing Firestore queries, or when the application elevates its own credentials to perform actions on behalf of a user without explicit checks.

Real-world attack patterns include enumeration through timing differences or error messages when documents exist but are unauthorized, and horizontal privilege escalation when user A can modify user B's data by guessing or iterating IDs. These map directly to OWASP API Top 10 A01:2023 broken access control and can violate compliance requirements such as GDPR and SOC2. Firestore-specific concerns include over-permissive service account bindings and missing ownership checks in queries, which can allow an attacker who compromises a lower-privilege API key to traverse datasets.

Remediation centers on ensuring every Firestore operation is gated by explicit, user-centric authorization checks in your Actix handlers. Never rely solely on Firestore security rules for multi-tenant isolation, and never trust path or query parameters without verifying ownership.

First, structure your Firestore data with user ownership baked into the document path or a field. A common pattern is to store user-specific data under a collection keyed by user ID, for example users/{user_id}/profile. This naturally limits the scope of queries and makes it easier to enforce that a request can only touch resources under its own user ID prefix.

use actix_web::{web, HttpResponse, Result};
use google_cloud_firestore::client::Client;
use google_cloud_firestore::firestore::document::Document;

async fn get_user_profile(
    path: web::Path,
    user_identity: String, // derived from your auth/session layer
    client: web::Data<Client>,
) -> Result<HttpResponse> {
    let requested_user_id = path.into_inner();
    // Ensure the authenticated user can only access their own profile
    if requested_user_id != user_identity {
        return Ok(HttpResponse::Forbidden().body("Unauthorized"));
    }
    let doc_path = format!("users/{}/profile", requested_user_id);
    let doc: Document = client.get_document(&doc_path).await.map_err(|e| {
        actix_web::error::ErrorInternalServerError(e.to_string())
    })?;
    Ok(HttpResponse::Ok().json(doc))
}

Second, when modeling one-to-many relationships, embed the user ID in the document or use collection group queries with an equality filter on the user field, then enforce that filter in application code as well. For example, to list a user’s orders:

async fn list_user_orders(
    user_identity: String,
    client: web::Data<Client>,
) -> Result<HttpResponse> {
    // Use collection group + field filter to scope to the user's orders
    let orders = client
        .collection_group("orders")
        .filter("user_id", "==", &user_identity)
        .limit(50)
        .get()
        .await
        .map_err(|e| actix_web::error::ErrorInternalServerError(e.to_string()))?;
    Ok(HttpResponse::Ok().json(orders))
}

Third, validate and sanitize any document IDs or query parameters before using them in Firestore paths to prevent injection or path traversal. Combine this with robust authentication (e.g., validated JWTs) so that user_identity is trustworthy. For broader protection, apply the Pro plan’s continuous monitoring and GitHub Action integration to fail CI/CD pipelines if risk scores indicate missing authorization checks, and use the Dashboard to track remediation over time.