Stack Overflow in Axum with Dynamodb

When building a Rust web service with Axum that uses DynamoDB as a backend, stack overflow risks arise primarily from unbounded recursion in data structures and from improper handling of deeply nested or large DynamoDB attribute values. In Axum, handler inputs are deserialized from JSON requests into Rust structures. If the deserialization logic allows recursive types without depth limits, or if the application directly reflects DynamoDB attribute values back to clients without validation, an attacker can craft payloads that trigger excessive stack usage during deserialization or serialization. This can lead to denial of service through stack exhaustion.

DynamoDB itself does not inherently cause stack overflow, but its attribute format can represent deeply nested maps and lists. An API that reflects DynamoDB items directly to clients (for example, returning an item read from a table) can expose recursive or extremely deep structures if the data was maliciously inserted or mis-modeled. In Axum, if the response serialization (e.g., using serde_json) traverses these nested structures without guardrails, the runtime stack can overflow. This is especially relevant when using the AWS SDK for Rust, where deserialization of DynamoDB attribute values into strongly-typed structs may recursively traverse nested maps if the types are not carefully bounded.

Additionally, query parsing and request validation in Axum can exacerbate the issue. For example, if path parameters or query strings are used to construct DynamoDB key conditions without validating depth or size, and the resulting item structures are recursively serialized in error messages or debugging endpoints, the combination creates a pathway for stack-based attacks. The risk is not in DynamoDB itself but in how Axum handlers convert between HTTP representations and database attribute values without enforcing depth limits or using iterative traversal for serialization.

Real-world patterns that increase exposure include: using serde with untagged enums that can nest recursively, directly serializing DynamoDB attribute maps into HTTP responses, and building recursive data access patterns in domain models. These patterns are common when developers map DynamoDB items 1:1 to Rust structs without considering maliciously deep input. The OWASP API Top 10 category '2023-A1: Broken Object Level Authorization' and '2023-A9: Security Misconfiguration' are relevant when recursive data flows are not constrained.

To detect this risk profile, scanning an Axum service backed by DynamoDB with middleBrick will surface findings related to Input Validation and Property Authorization, highlighting unbounded recursion risks and missing depth controls. The scanner evaluates whether responses can contain deeply nested structures and whether the API surface reflects raw database attribute formats without sanitization.

Apply explicit depth and size limits when deserializing DynamoDB attribute values in Axum handlers. Do not directly expose raw DynamoDB attribute maps as HTTP responses. Instead, define bounded Data Transfer Objects (DTOs) and validate nested depths before serialization. Use iterative or bounded traversal when converting DynamoDB items to domain models.

Example: Safe deserialization with depth control using the AWS SDK for Rust and Serde.

use aws_sdk_dynamodb::types::AttributeValue;
use serde::Deserialize;
use std::collections::HashMap;

/// Recursively compute depth of a DynamoDB AttributeValue, with a hard limit.
fn depth_of(value: &AttributeValue, limit: usize) -> usize {
    if limit == 0 {
        return limit + 1;
    }
    match value {
        AttributeValue::M(map) => {
            1 + map.values()
                .map(|v| depth_of(v, limit.saturating_sub(1)))
                .max()
                .unwrap_or(0)
        }
        AttributeValue::L(list) => {
            1 + list.iter()
                .map(|v| depth_of(v, limit.saturating_sub(1)))
                .max()
                .unwrap_or(0)
        }
        _ => 1,
    }
}

/// Deserialize an AttributeValue into a generic serde_json::Value with a depth cap.
fn bounded_deserialize(value: &AttributeValue, max_depth: usize) -> Result {
    if depth_of(value, max_depth) > max_depth {
        return Err(format!("Attribute depth exceeds maximum allowed depth of {}", max_depth));
    }
    // Convert AttributeValue to JSON Value safely; in production, handle errors explicitly.
    let json = serde_dynamodb::from_attrs(value.clone()).map_err(|e| e.to_string())?;
    Ok(json)
}

#[derive(Deserialize)]
struct Profile {
    user_id: String,
    /// Ensure nested structures are bounded by DTOs, not raw AttributeValue maps.
    settings: Settings,
}

#[derive(Deserialize)]
struct Settings {
    theme: String,
    notifications: bool,
}

/// Axum handler example with safe DynamoDB item retrieval.
async fn get_profile(
    id: String,
    client: aws_sdk_dynamodb::Client,
) -> Result {
    let resp = client
        .get_item()
        .table_name("profiles")
        .key("user_id", AttributeValue::S(id))
        .send()
        .await
        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;

    let item = resp.item().ok_or_else(|| (StatusCode::NOT_FOUND, "Profile not found".to_string()))?;

    // Validate depth before converting to domain type.
    let json = bounded_deserialize(item, 5).map_err(|e| (StatusCode::BAD_REQUEST, e))?;
    let profile: Profile = serde_json::from_value(json).map_err(|e| (StatusCode::BAD_REQUEST, e.to_string()))?;

    Ok(Json(profile))
}

Example: Explicitly limit recursion in serialization for error responses and logging.

/// Safely serialize a DynamoDB item for logging, avoiding deep recursion.
fn safe_log_dynamo_item(item: &HashMap) -> serde_json::Value {
    // Use a custom serializer or bounded conversion to avoid deep nesting in logs.
    // This example uses serde_dynamodb but assumes bounded structures.
    // In practice, prefer iterative conversion for deeply nested or untrusted data.
    serde_dynamodb::to_value(item.clone()).unwrap_or_else(|_| json!({"error": "failed to serialize"}))
}

When using middleBrick to scan this Axum + DynamoDB service, the dashboard will highlight findings in categories such as Input Validation and Property Authorization, and the CLI output will include specific remediation guidance tied to these patterns.

For continuous assurance, add the GitHub Action to fail builds if the API security score drops below your chosen threshold, ensuring that recursive or unsafe data handling patterns are caught before deployment.