Insecure Deserialization in Rocket with Firestore

Insecure deserialization occurs when an application accepts serialized data from an untrusted source and reconstructs objects without sufficient validation. In a Rocket application that uses Google Cloud Firestore, this typically surfaces in endpoints that accept JSON payloads intended to map to Firestore document structures or custom Rust structs via Serde deserialization.

Firestore documents are often deserialized into strongly typed structs using Serde. If the application directly deserializes user-controlled input (e.g., JSON request bodies) into these structs and then writes or reads from Firestore based on that data, it may be vulnerable to crafted payloads that manipulate the deserialization process. For example, an attacker could send carefully designed JSON that, when deserialized, results in unexpected types or deeply nested structures that cause excessive memory consumption or logic bypasses.

Consider a Rocket route that accepts a document ID and a JSON patch to update a Firestore document. If the patch payload is deserialized using a generic Serde value (e.g., serde_json::Value) and then merged into the document without strict schema validation, an attacker could inject fields that change behavior on deserialization side effects, especially when combined with polymorphic deserialization patterns. Though Firestore itself does not execute deserialized code, the downstream logic that interprets the deserialized objects may take unsafe actions, such as condition checks that are bypassed or privilege escalation paths.

Another vector involves public endpoints that retrieve documents and deserialize them into application-specific types without validating the presence of expected fields. Missing or altered fields in the deserialized object may lead to insecure defaults or logic errors, which can be chained with other checks like authentication or authorization (BOLA/IDOR) to escalate impact.

In a real assessment using middleBrick, insecure deserialization findings in a Rocket + Firestore setup are surfaced alongside related checks such as Input Validation and Property Authorization. The scanner sends targeted payloads designed to trigger unexpected deserialization behavior and maps findings to the OWASP API Top 10 and relevant compliance frameworks, providing prioritized remediation guidance without requiring authentication.

To mitigate insecure deserialization risks in a Rocket application using Firestore, enforce strict schema validation and avoid generic deserialization of untrusted input. Prefer strongly typed structs with explicit field definitions and validate all inputs before using them in Firestore operations.

Below are concrete Rust code examples using Rocket and the Firestore client library.

1. Use strongly typed structs with Serde and validate required fields

use rocket::serde::{json::Json, Deserialize, Serialize};
use google_cloud_firestore::client::Client;
use serde::Deserialize;

#[derive(Debug, Deserialize, Serialize)]
struct UserProfile {
    user_id: String,
    display_name: String,
    email: String,
    #[serde(default)]
    preferences: Preferences,
}

#[derive(Debug, Deserialize, Serialize, Default)]
struct Preferences {
    theme: String,
    notifications_enabled: bool,
}

#[rocket::post("/profile", format = "json", data = "<input>")]
async fn update_profile(
    client: &State<Client>,
    input: Json<UserProfile>,
) -> Result<rocket::response::status::Ok, rocket::response::status::BadRequest<String>> {
    let profile = input.into_inner();

    // Validate required fields before using Firestore
    if profile.user_id.is_empty() || profile.display_name.is_empty() || profile.email.is_empty() {
        return Err(rocket::response::status::BadRequest(
            "Missing required fields".to_string(),
        ));
    }

    let doc_ref = client.collection("profiles").doc(&profile.user_id);
    let firestore_data = serde_json::to_value(&profile).map_err(|e| {
        rocket::response::status::BadRequest(format!("Serialization error: {e}"))
    })?;

    doc_ref.set(firestore_data).await.map_err(|e| {
        rocket::response::status::BadRequest(format!("Firestore error: {e}"))
    })?;

    Ok(rocket::response::status::Ok(()))
}

This approach ensures that only expected fields are accepted and that Firestore writes use a validated, serializable structure.

2. Avoid generic deserialization for update operations

Instead of accepting serde_json::Value for arbitrary patches, define an allowed set of update operations and validate each field.

use rocket::serde::json::Value;
use std::collections::HashMap;

#[rocket::post("/profile/<user_id>", format = "json", data = "<patch>")]
async fn patch_profile(
    client: &State<Client>,
    user_id: String,
    patch: Json<Value>,
) -> Result<(), &'static str> {
    // Validate patch structure explicitly
    let obj = patch.as_object().ok_or("Patch must be a JSON object")?;

    let mut updates: HashMap<String, Value> = HashMap::new();
    for (key, value) in obj {
        match key.as_str() {
            "display_name" | "email" | "theme" | "notifications_enabled" => {
                // Type checks per field can be added here
                updates.insert(key.clone(), value.clone());
            }
            _ => return Err("Field not allowed in patch"),
        }
    }

    let doc_ref = client.collection("profiles").doc(&user_id);
    doc_ref.update(updates).await.map_err(|_| "Firestore update failed")?;
    Ok(())
}

By explicitly allowing only known fields and avoiding pass-through deserialization of arbitrary JSON, you reduce the risk of malformed or malicious payloads affecting Firestore operations.

middleBrick scans such endpoints and flags insecure deserialization patterns alongside input validation and authorization checks, providing actionable remediation steps that align with frameworks like OWASP API Top 10.