Mass Assignment in Axum with Dynamodb

Mass assignment occurs when an API binds incoming request data directly to data model fields without explicit allowlisting. In an Axum application that uses Amazon DynamoDB as the persistence layer, this typically manifests at two layers: the Rust data model (structs) and the DynamoDB attribute-value representation. If deserialization (for example using serde_dynamo or a manual mapping layer) maps request JSON keys into DynamoDB attribute names without filtering, an attacker can supply unexpected keys to create or overwrite attributes that the application logic does not intend to be set.

Consider an Axum handler that accepts a JSON payload and writes it to DynamoDB via a high-level helper. A common unsafe pattern is to deserialize the request into a HashMap or a strongly typed struct that mirrors DynamoDB attribute names, then forward that map directly to a PutItem or UpdateItem call. Because DynamoDB is schemaless, any extra top-level or nested attributes are accepted and persisted. If the handler does not validate or project only intended fields, an attacker can inject attributes such as admin, permissions, or internal metadata keys, effectively escalating privileges or bypassing authorization checks enforced at the application layer.

Compounded by typical Axum extractor usage, mass assignment can occur even when developers believe they are being safe. For example, using Json(TodoInput { title, description }) may appear limited, but if the struct derives Deserialize broadly or is constructed manually from a Value, fields like is_admin or owner_id can be added if the incoming JSON contains them. When the handler later writes this struct’s fields to DynamoDB via attribute name mapping, any unchecked field becomes a persistence vector. Because DynamoDB does not enforce a schema at write time, these injected attributes remain stored and can be returned in subsequent reads, enabling horizontal or vertical privilege escalation (BOLA/IDOR and BFLA) depending on how item-level permissions are implemented.

Another specific risk arises when the application uses DynamoDB expressions (e.g., UpdateExpression with SET) built from user-controlled input. If the expression attribute names or values are derived without strict allowlisting, an attacker can manipulate conditional writes or introduce new attributes. For example, a crafted payload could include keys that alter condition expressions or inject additional SET clauses, leading to unintended updates across multiple attributes. Because the Axum layer may not validate which attributes are mutable, the DynamoDB layer executes the request as formulated, making mass assignment a pathway to both data tampering and privilege escalation in serverless or containerized deployments.

Remediation focuses on explicit projection, strict deserialization, and defensive handling of DynamoDB attribute mappings. Below are concrete, realistic patterns for Axum that prevent mass assignment when interacting with DynamoDB.

1) Strongly typed request structs with #[serde(deny_unknown_fields)]

Define input structs that explicitly list allowed fields and reject any unknown keys at deserialization time. This prevents attackers from injecting unexpected attributes that could map to DynamoDB attribute names.

use serde::{Deserialize, Serialize};

#[derive(Deserialize, Serialize)]
#[serde(deny_unknown_fields)]
pub struct CreateItemRequest {
    pub title: String,
    pub description: String,
}

2) Manual projection before DynamoDB attribute conversion

Instead of mapping deserialized JSON directly to AttributeValue, convert only the fields you intend to store. This ensures nested or unexpected keys are not forwarded to DynamoDB.

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

fn project_to_dynamodb(item: CreateItemRequest) -> HashMap<String, AttributeValue> {
    let mut map = HashMap::new();
    map.insert("title".to_string(), AttributeValue::S(item.title));
    map.insert("description".to_string(), AttributeValue::S(item.description));
    // Intentionally omitting any other fields
    map
}

3) Use DynamoDB ExpressionAttributeNames safely

When using update expressions, avoid concatenating user input into expression attribute names. Use a fixed mapping and validate placeholders against a known allowlist.

use aws_sdk_dynamodb::types::AttributeValue;

fn update_item_safe(id: String, updates: HashMap<String, AttributeValue>) -> String {
    // Only allow known, safe attribute names
    let allowed = ["title", "description", "version"];
    let mut update_expr = String::from("SET ");
    let mut first = true;
    for (key, value) in updates {
        if allowed.contains(&key.as_str()) {
            if !first {
                update_expr.push_str(", ");
            }
            update_expr.push_str(&format!("#attr{} = :val{}", key, key));
            first = false;
        }
    }
    // In practice, pass ExpressionAttributeNames and ExpressionAttributeValues separately
    update_expr
}

4) Validate and sanitize nested structures

If your items contain nested maps or lists, ensure each level is validated or transformed explicitly rather than accepting raw JSON values that could contain injected attributes.

use serde_json::Value;

fn sanitize_nested(value: &Value) -> Option<HashMap<String, AttributeValue>> {
    let obj = value.as_object()?;
    let mut map = HashMap::new();
    for (k, v) in obj {
        if ["allowed_field1", "allowed_field2"].contains(&k.as_str()) {
            map.insert(k.clone(), AttributeValue::S(v.to_string()));
        }
    }
    Some(map)
}

5) Prefer DynamoDB condition expressions for authorization-sensitive updates

Even after projection, use conditional writes to enforce ownership or state constraints at the database level, reducing impact should application-layer filtering be bypassed.

let condition = aws_sdk_dynamodb::types::ConditionExpression::builder()
    .expression_attribute_names(std::iter::once(("#owner", AttributeValue::S("owner_id".to_string()))))
    .expression_attribute_values(std::iter::once((":uid", AttributeValue::S("user-uuid".to_string()))))
    .condition_expression("attribute_exists(#owner) AND #owner = :uid")
    .build();

By combining strict Rust type safety, explicit projection, and cautious use of DynamoDB expressions, you eliminate mass assignment vectors while still leveraging DynamoDB’s schemaless flexibility for intended attributes only.