Out Of Bounds Write in Axum with Dynamodb

An Out Of Bounds Write occurs when an application writes data beyond the intended memory boundaries or, in the context of API and database interactions, writes data beyond expected constraints such as length limits or partition key structures. When using Axum with DynamoDB, this typically manifests as unchecked user input used to construct DynamoDB key expressions, item sizes, or attribute values that exceed service limits or application logic boundaries.

DynamoDB has strict limits: item size is capped at 400 KB, and partition key and sort key values are constrained by length and type expectations. In Axum handlers, if input is bound directly to DynamoDB keys or attributes without validation, an attacker can supply oversized payloads or malformed identifiers that push writes beyond intended structures. This can corrupt item layouts, trigger conditional check failures, or cause write operations to target incorrect items when index expressions or key schemas are derived from unchecked inputs.

For example, consider an endpoint that uses a user-supplied identifier as a partition key without length validation. An oversized identifier can cause the serialized item to exceed DynamoDB’s 400 KB limit, resulting in a failed write that may be misinterpreted by Axum error handling as a partial or inconsistent state. Similarly, numeric overflow in quantity fields used in update expressions can cause wraparound values, leading to unintended negative quantities or excessive increments that violate business logic boundaries.

In a black-box scan using middleBrick, such misconfigurations are surfaced under BFLA/Privilege Escalation and Input Validation checks. The scanner probes endpoints with oversized strings, boundary integers, and malformed key structures, observing whether DynamoDB rejects writes with ProvisionedThroughputExceeded or ValidationException, or whether Axum inadvertently accepts malformed payloads. The combination of Axum’s flexible routing and DynamoDB’s strict schema and size constraints amplifies the impact of missing validation, as unchecked inputs can directly shape low-level write operations.

To illustrate, an unsafe Axum handler might directly bind JSON fields to DynamoDB attribute values without sanitization. An attacker sending a 500 KB string for a text attribute can force the item size beyond DynamoDB’s limit, causing the write to fail and potentially exposing stack traces or internal paths through Axum’s error responses. middleBrick’s LLM/AI Security checks also verify whether such endpoints expose system prompts or error details that could aid further exploitation.

Remediation focuses on strict input validation, size checks, and defensive coding patterns in Axum before constructing DynamoDB requests. Always validate string lengths against DynamoDB limits (e.g., attribute values ≤ 64 KB for strings, total item ≤ 400 KB), and enforce type constraints on keys.

Use extractor guards in Axum to validate incoming payloads. For partition keys and sort keys, enforce maximum lengths and acceptable character sets. For numeric fields, use saturating arithmetic to prevent overflow and validate ranges before using them in update expressions.

Below is a correct Axum handler example that validates input before constructing a DynamoDB PutItem request using the official AWS SDK for Rust. It enforces length limits on string attributes and validates numeric ranges to prevent out-of-bounds writes.

use axum::{routing::post, Router};
use aws_sdk_dynamodb::Client;
use serde::{Deserialize, Serialize};

const MAX_STRING_LENGTH: usize = 64 * 1024; // DynamoDB string limit guidance
const MAX_ITEM_SIZE_BYTES: usize = 400 * 1024; // DynamoDB item size limit

#[derive(Deserialize, Serialize)]
struct ItemInput {
    pk: String,
    sk: String,
    data: String,
    quantity: i64,
}

async fn create_item(
    input: axum::extract::Json,
    client: axum::extract::State,
) -> Result, (axum::http::StatusCode, String)> {
    let input = input.into_inner();

    // Validate key lengths
    if input.pk.len() > MAX_STRING_LENGTH || input.sk.len() > MAX_STRING_LENGTH {
        return Err((axum::http::StatusCode::BAD_REQUEST, "Key length exceeds limit".to_string()));
    }

    // Validate data length
    if input.data.len() > MAX_STRING_LENGTH {
        return Err((axum::http::StatusCode::BAD_REQUEST, "Data length exceeds limit".to_string()));
    }

    // Validate total item size (simplified estimation)
    let estimated_size = input.pk.len() + input.sk.len() + input.data.len() + 40; // metadata overhead
    if estimated_size > MAX_ITEM_SIZE_BYTES {
        return Err((axum::http::StatusCode::BAD_REQUEST, "Item size exceeds DynamoDB limit".to_string()));
    }

    // Validate quantity range to prevent overflow/wraparound
    if input.quantity < 0 || input.quantity > 1_000_000 {
        return Err((axum::http::StatusCode::BAD_REQUEST, "Quantity out of valid range".to_string()));
    }

    let item = aws_sdk_dynamodb::types::AttributeValue::from(
        serde_dynamodb::to_hashmap(&input).map_err(|e| (axum::http::StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?,
    );

    client
        .put_item()
        .table_name("ItemsTable")
        .set_item(Some(item))
        .send()
        .await
        .map_err(|e| (axum::http::StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;

    Ok(axum::response::Json(()))
}

fn app() -> Router {
    let client = Client::new(&aws_config::load_from_env().await);
    Router::new()
        .route("/items", post(move |input| create_item(input, client.clone())))
}

This pattern ensures that Axum rejects malformed or oversized inputs before they reach DynamoDB, reducing the chance of an out-of-bounds write. middleBrick’s CLI can be used to verify that such validation is reflected in the runtime behavior by scanning the endpoint and checking whether oversized payloads are rejected with 400-level responses rather than causing unexpected DynamoDB errors.

For continuous protection, use the middleBrick Pro plan to enable continuous monitoring and integrate the GitHub Action to fail CI/CD builds if a scan detects missing length checks or validation gaps. The MCP Server allows AI coding assistants in your IDE to flag unsafe DynamoDB write patterns during development, aligning with frameworks like OWASP API Top 10 and PCI-DSS requirements for input validation.