Stack Overflow in Axum with Firestore

A stack overflow in an Axum service that uses Firestore typically arises when recursive or deeply nested data structures are deserialized from Firestore documents and then processed without depth limits. Firestore documents can contain maps, arrays, and nested objects; if an API endpoint directly mirrors this structure into Rust structs and then performs recursive operations (e.g., walking a tree of comments or permissions), an attacker can craft data that causes unbounded recursion. Because Axum deserializes request bodies into strongly typed structures, malicious payloads that nest maps or arrays deeply enough can overflow the call stack during deserialization or subsequent processing, leading to a denial of service.

Another vector specific to the Axum + Firestore combination is unbounded recursion in application logic that traverses Firestore references. For example, a document representing an organizational hierarchy might store parent references or child arrays. If an endpoint recursively follows these references to build a tree and does not enforce depth or cycle limits, a crafted document can create cycles or extreme depth. Axum’s extractor pattern (e.g., using Json<T> or FromRequest) will deserialize the incoming JSON into T before any recursion guard is applied, so the stack can grow unchecked during traversal. This exposes a denial-of-service surface aligned with the BFLA/Privilege Escalation and Input Validation checks in middleBrick’s 12 parallel security scans, which look for unsafe consumption patterns and input validation gaps.

middleBrick’s scans detect these risks by analyzing the unauthenticated attack surface of Axum endpoints that consume Firestore-like payloads. It tests input validation and unsafe consumption checks by probing deeply nested JSON and recursive structures, flagging missing depth limits or missing cycle detection. The scanner does not assume Axum’s runtime behavior but validates whether the API surface accepts inputs that could trigger stack exhaustion. Findings include severity-ranked guidance on how to constrain recursion and validate input structure, mapped to OWASP API Top 10 and Input Validation failures.

To remediate stack overflow risks when using Firestore data in Axum, bound recursion and validate depth before processing nested structures. Use explicit depth checks and iterative traversal instead of naive recursion. Below are concrete Rust examples for Axum handlers that safely process Firestore-like documents.

use axum::{{
    extract::Json,
    response::IntoResponse,
    routing::post,
    Router,
}};
use serde::{Deserialize, Serialize};
use std::net::SocketAddr;

const MAX_DEPTH: usize = 10;

#[derive(Deserialize, Serialize, Debug)]
struct FirestoreDocument {
    data: DocumentData,
}

#[derive(Deserialize, Serialize, Debug)]
#[serde(untagged)]
enum DocumentData {
    Node(NodeData),
    NestedArray(Vec),
    Map(std::collections::HashMap),
}

#[derive(Deserialize, Serialize, Debug)]
struct NodeData {
    value: String,
    #[serde(default)]
    children: Vec,
}

async fn handle_document(Json(payload): Json) -> impl IntoResponse {
    if let Err(e) = validate_depth(&payload.data, 0) {
        return (axum::http::StatusCode::BAD_REQUEST, format!("Invalid input: {}", e));
    }
    // Safe to process
    (axum::http::StatusCode::OK, "valid")
}

fn validate_depth(data: &DocumentData, depth: usize) -> Result<(), String> {
    if depth > MAX_DEPTH {
        return Err(format!("Maximum nesting depth exceeded: {depth}"));
    }
    match data {
        DocumentData::Node(node) => {
            for child in &node.children {
                validate_depth(child, depth + 1)?;
            }
            Ok(())
        }
        DocumentData::NestedArray(items) => {
            for item in items {
                validate_depth(item, depth + 1)?;
            }
            Ok(())
        }
        DocumentData::Map(map) => {
            for (_, value) in map {
                validate_depth(value, depth + 1)?;
            }
            Ok(())
        }
    }
}

#[tokio::main]
async fn main() {
    let app = Router::new().route("/validate", post(handle_document));
    let addr = SocketAddr::from(([127, 0, 0, 1], 3000));
    axum::Server::bind(&addr)
        .serve(app.into_make_service())
        .await
        .unwrap();
}

This example enforces a constant MAX_DEPTH during recursive descent, ensuring that deeply nested Firestore documents cannot exhaust the stack. For production use, combine this with schema validation (e.g., using validator or custom checks) and avoid direct mirroring of Firestore’s flexible document model into recursive Rust enums without guards. middleBrick’s Pro plan supports continuous monitoring for such input validation issues, scanning APIs on a configurable schedule and integrating CI/CD gates via its GitHub Action to fail builds when risk thresholds are exceeded.

Additionally, prefer iterative algorithms (e.g., using an explicit stack) for traversing Firestore references to avoid recursion entirely. If your data model includes parent or child references, resolve cycles by tracking visited document IDs. These practices reduce the attack surface for stack exhaustion and align with the framework checks in middleBrick’s scans, which highlight insecure consumption patterns and missing authorization controls in endpoints handling nested data.