Format String in Axum with Dynamodb

A format string vulnerability occurs when user-controlled input is passed directly into a formatting function such as format! or println! in Rust without explicit format specifiers. In an Axum application that interacts with DynamoDB, this often happens when building request parameters or log messages using unchecked string concatenation or interpolation. For example, if a developer constructs a DynamoDB expression attribute values map using user input via format!, an attacker can supply format verbs such as %s, %x, or %n to read stack memory or potentially cause undefined behavior.

Consider a handler that builds a DynamoDB UpdateItem key using user-supplied values:

let user_supplied = "table_name";
let key = format!(\"USER#{}#PROFILE\", user_supplied);

If user_supplied contains format specifiers, the resulting string may be misinterpreted during logging or used indirectly in downstream serialization. More critically, if this string is later used in a DynamoDB condition expression built via string formatting, an attacker can manipulate the structure of the expression, leading to unexpected query behavior or data exposure.

In Axum, routes often deserialize JSON into structs and forward values to DynamoDB via the AWS SDK. If those values are logged using the log crate with unchecked formatting, such as:

info!(\"Processing request for user: {} \", user_id);

and user_id contains format placeholders, the logging subsystem may read arbitrary memory. This does not directly alter DynamoDB requests, but it reveals internal state or error paths that can be correlated with DynamoDB access patterns, aiding further exploitation.

The combination of Axum’s extractor-driven request handling and the AWS SDK for DynamoDB’s expression-based query syntax increases risk when developers treat user input as safe for string construction. Because DynamoDB operations often rely on condition expressions and attribute value placeholders, improperly sanitized input used to build these expressions can lead to malformed requests or information leakage through side channels, especially when paired with verbose or unchecked logging.

To prevent format string issues in an Axum service that uses DynamoDB, ensure that all user-controlled data is passed as structured data rather than interpolated strings. Use the official AWS SDK for Rust, which accepts strongly typed structures for DynamoDB operations, avoiding string formatting entirely for query construction.

Instead of building key strings with format!, construct partition and sort key values directly:

use aws_sdk_dynamodb::types::AttributeValue;

let partition_key = AttributeValue::S(format!(\"USER#{}#PROFILE\", sanitize_user_input(&user_id)));

Even better, avoid runtime string construction for keys by using constants or enums, and sanitize input with a dedicated validation layer before it reaches the formatter:

fn sanitize_user_input(input: &str) -> String {
    input.replace(['%', '\n', '\r'], "")
}

When logging, use structured logging with the tracing crate and named fields rather than interpolated strings:

info!(user_id = %user_id, \"Processing request\");

This prevents the logging backend from misinterpreting user input as format directives. For DynamoDB condition expressions, use the SDK’s expression builder to keep data and expression logic separate:

let expr = aws_sdk_dynamodb::types::ConditionExpression::builder()
    .expression("#status = :val")
    .expression_attribute_names({
        let mut m = std::collections::HashMap::new();
        m.insert("#status", "status");
        m
    })
    .expression_attribute_values({
        let mut m = std::collections::HashMap::new();
        m.insert(":val", AttributeValue::S("active".to_string()));
        m
    })
    .build()
    .unwrap();

By relying on typed structures and expression builders, you eliminate the need for manual string formatting where format string vulnerabilities could occur. The AWS SDK ensures that values are transmitted safely without concatenation into raw query strings.

In Axum, route handlers should validate and transform incoming data before it reaches any DynamoDB interaction layer. Combine this with middleware that enforces structured logging and input normalization to reduce the attack surface across the request lifecycle.