Prototype Pollution in Axum with Dynamodb

Prototype pollution in an Axum application that interacts with DynamoDB occurs when user-controlled input is merged into objects used to build requests or deserialize responses, allowing an attacker to modify inherited properties on JavaScript objects (in a frontend) or, server-side, to affect object creation and behavior in Rust before data is serialized for DynamoDB. Although Rust is memory-safe and does not have JavaScript-style prototypes, prototype pollution in this context refers to the injection of unexpected fields like __proto__, constructor, or prototype into JSON payloads that later influence object instantiation, validation logic, or serialization. In Axum, handlers often deserialize JSON into strongly typed structs using Serde. If the application merges or extends these structs with untrusted data—such as using serde_json::Value for dynamic fields or custom merging logic—an attacker can supply properties that affect how data is interpreted or passed to DynamoDB.

When the poisoned data reaches DynamoDB operations, it may alter request construction. For example, if the application builds a PutItem or UpdateItem request using a dynamic map that includes injected fields, those fields could change the semantics of item attributes or be stored in the database. DynamoDB itself does not execute prototype pollution, but the pollution occurs in the application layer before data is sent, potentially leading to privilege escalation (via modified role or permission attributes), data integrity issues, or bypass of validation checks. In an OpenAPI/Swagger workflow analyzed by middleBrick, unsafe consumption of untrusted fields without a strict allowlist can correlate with BFLA/Privilege Escalation findings, and the scanner’s Property Authorization checks help detect missing authorization on sensitive attributes.

Consider an Axum handler that accepts a JSON payload and forwards it to DynamoDB without strict schema enforcement:

use axum::{routing::post, Json, Router};
use serde_json::Value;
use aws_sdk_dynamodb::Client;

async fn create_item(Json(body): Json, client: &Client) -> Result<(), (StatusCode, String)> {
    let mut item = serde_json::map::Map::new();
    // Unsafe merge: attacker can inject fields like __proto__ or role
    for (k, v) in body.as_object().ok_or((StatusCode::BAD_REQUEST, "invalid"))? {
        item.insert(k.clone(), v.clone());
    }
    let request = aws_sdk_dynamodb::model::PutItemRequestBuilder::default()
        .set_table_name(Some("Items".to_string()))
        .set_item(item)
        .build()
        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    client.send_request(&request).await.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    Ok(())
}

If an attacker sends {"name": "alice", "__proto__": {"role": "admin"}}, the merged map may propagate unwanted properties into the DynamoDB item, depending on downstream usage. middleBrick’s LLM/AI Security checks do not apply here, but its authentication and property authorization checks can highlight missing constraints. To mitigate, validate incoming JSON against an allowlist schema and avoid dynamic merging into request builders.

Remediation focuses on strict schema validation, avoiding unsafe merging, and ensuring DynamoDB operations use explicit, typed structures. Prefer strongly-typed structs with Serde and reject unknown fields. This prevents attacker-supplied properties such as __proto__ or constructor from entering the item map.

Use serde(deny_unknown_fields) to cause deserialization to fail if unexpected properties are present:

use serde::{Deserialize, Serialize};

#[derive(Debug, Deserialize, Serialize)]
#[serde(deny_unknown_fields)]
struct Item {
    id: String,
    name: String,
    role: String,
}

async fn create_item_typed(Json(body): Json, client: &Client) -> Result {
    let item = aws_sdk_dynamodb::model::PutItemRequestBuilder::default()
        .set_table_name(Some("Items".to_string()))
        .set_item(serde_dynamodb::to_hashmap(&body).map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?)
        .build()
        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    client.send_request(&item).await.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    Ok((StatusCode::CREATED, "created"))
}

If you must handle dynamic fields, isolate them and explicitly map only allowed keys instead of merging blindly:

use serde_json::Map;

fn sanitize_item(raw: Map<String, serde_json::Value>) -> Result {
    let allowed = ["id", "name", "attributes"];
    let mut out = Map::new();
    for (k, v) in raw {
        if allowed.contains(&k.as_str()) {
            out.insert(k, v);
        }
    }
    Ok(out)
}

async fn create_item_sanitized(Json(body): Json>, client: &Client) -> Result<(), (StatusCode, String)> {
    let item = sanitize_item(body)?;
    let request = aws_sdk_dynamodb::model::PutItemRequestBuilder::default()
        .set_table_name(Some("Items".to_string()))
        .set_item(item)
        .build()
        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    client.send_request(&request).await.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;
    Ok(())
}

For DynamoDB-specific modeling, use serde_dynamodb to convert structs to attribute maps safely. This avoids manual map manipulation where injected fields could slip through. Combine this with Axum’s rejection handling to return 400 on malformed input, and enforce property-level authorization in your handlers to ensure sensitive attributes like role are not user-controlled.

middleBrick’s Pro plan can support continuous monitoring for endpoints that interact with DynamoDB, providing per-category breakdowns and prioritized findings that map to frameworks such as OWASP API Top 10 and SOC2. Its CLI allows quick scans from the terminal with middlebrick scan <url>, and the GitHub Action can add API security checks to your CI/CD pipeline, failing builds if risk scores drop below your chosen threshold.