Token Leakage in Axum with Dynamodb

Token leakage in an Axum service that uses DynamoDB as a persistence layer typically occurs when authentication tokens, session identifiers, or API keys are inadvertently stored, logged, or reflected in DynamoDB items. In this combination, the application may write request-scoped tokens into DynamoDB tables for tracking, audit, or caching, and later expose them through API responses or logs. Because DynamoDB is often used as a backend data store for session or credential storage, tokens can become long-lived data objects that increase the blast radius if access controls are misconfigured or if low-sensitivity items are returned without proper authorization checks.

For example, an Axum handler that authenticates a user and stores a bearer token in a DynamoDB table for revocation or introspection might inadvertently include that token in responses or logs if serialization is too permissive or if debug endpoints expose the item. In black-box scanning, middleBrick checks for such exposures across the unauthenticated attack surface, including endpoints that interact with DynamoDB-backed resources. If the API returns DynamoDB item representations that include token fields, an attacker could harvest credentials used elsewhere in the system.

Additionally, token leakage can stem from insufficient input validation when constructing DynamoDB queries. An attacker may supply crafted parameters that cause the application to retrieve items containing sensitive tokens, especially if primary key design inadvertently exposes token attributes. The risk is compounded when responses include entire DynamoDB records without filtering out sensitive attributes. middleBrick’s checks for Data Exposure and Property Authorization evaluate whether token-like values appear in outputs, and whether authorization boundaries prevent unauthorized retrieval of items that contain such values.

Another vector involves logging or error messages that include token values when DynamoDB operations fail or are retried. In Axum, if developers log request or response structs that embed token fields before returning errors, tokens can leak into log stores or monitoring systems. middleBrick’s Data Exposure checks look for sensitive patterns such as API keys and tokens in runtime outputs, including responses that mirror DynamoDB item contents. The scanner also tests for BFLA and Privilege Escalation risks where token-bearing items might be accessible across user boundaries due to weak ownership checks.

LLM/AI Security checks performed by middleBrick do not directly detect token leakage in DynamoDB, but they help identify whether system prompts or generated text inadvertently expose token values through API outputs. This is relevant when APIs return structured data that includes tokens as part of larger payloads. The scanner validates that outputs do not contain leaked credentials, ensuring that token fields are not reflected in responses or documentation generated from runtime behavior.

Finally, insecure consumption patterns in Axum handlers that deserialize DynamoDB responses into generic maps or structs can propagate tokens into downstream services or caches. If the application constructs URLs or messages using token-bearing attributes without redaction, tokens may be transmitted over less-secure channels. middleBrick tests for Unsafe Consumption by verifying that sensitive attributes are not unnecessarily propagated through logs, URLs, or external integrations, helping teams understand how DynamoDB-backed Axum services can unintentionally expose authentication material.

To remediate token leakage in Axum with DynamoDB, focus on preventing tokens from being written, stored, or returned in ways that increase exposure. Use attribute-level filtering when serializing DynamoDB items, ensure that token fields are excluded from responses, and apply strict ownership checks before retrieving items. The following approaches and code examples demonstrate concrete protections.

1. Exclude tokens from DynamoDB writes

When storing session or authentication data, avoid placing raw tokens into DynamoDB. Instead, store a salted hash or a reference identifier. If you must store tokens, ensure they are encrypted at rest and never returned to clients. The example below shows how to write an item without including a token field.

use aws_sdk_dynamodb::Client;
use serde::{Deserialize, Serialize};

#[derive(Serialize, Deserialize)]
struct SessionRecord {
    user_id: String,
    session_id: String,
    // Intentionally omit token field
}

async fn save_session(client: &Client, record: &SessionRecord) -> Result<(), aws_sdk_dynamodb::Error> {
    client
        .put_item()
        .table_name("sessions")
        .set_item(Some(record.clone().into()))
        .send()
        .await?;
    Ok(())
}

2. Filter sensitive attributes on read

When retrieving items from DynamoDB, project only the necessary attributes and omit token fields. This reduces the risk of accidental exposure through logs or responses.

async fn get_session(client: &Client, session_id: &str) -> Result, aws_sdk_dynamodb::Error> {
    let resp = client
        .get_item()
        .table_name("sessions")
        .key("session_id", session_id.into())
        .projection_expression("user_id, session_id") // explicitly exclude token attributes
        .send()
        .await?;

    Ok(resp.item.map(|item| /* deserialize */ unimplemented!()))
}

3. Enforce ownership checks before access

Ensure that any DynamoDB item access includes a check that the requesting user owns the item. Combine this with fine-grained IAM policies to restrict who can read items that may contain sensitive data.

async fn get_user_session(client: &Client, user_id: &str, session_id: &str) -> Result, aws_sdk_dynamodb::Error> {
    let key = aws_sdk_dynamodb::types::AttributeValue::from(session_id);
    let resp = client
        .get_item()
        .table_name("sessions")
        .key("session_id", key)
        .send()
        .await?;

    if let Some(item) = resp.item {
        // Verify ownership attribute matches requesting user_id
        if let Some(stored_user_id) = item.get("user_id").and_then(|v| v.as_str()) {
            if stored_user_id == user_id {
                return Ok(Some(/* deserialize */ unimplemented!()));
            }
        }
    }
    Ok(None)
}

4. Redact tokens in logs and errors

Ensure that logging or error handling in Axum does not include token values. Use structured logging with explicit field exclusion and sanitize any debug output that might include DynamoDB item contents.

use tracing::info;

fn log_session_action(session_id: &str, user_id: &str) {
    // Avoid logging token fields; use identifiers only
    info!(session_id = session_id, user_id = user_id, "session accessed");
}

5. Apply least privilege to DynamoDB access

Configure IAM roles and policies so that the Axum service can only perform necessary operations on specific DynamoDB tables and attributes. Avoid broad permissions that allow read/write of token-containing items.