Token Leakage in Actix with Dynamodb

Token leakage in an Actix application that uses DynamoDB typically occurs when authentication tokens or session identifiers are mishandled in request processing, logging, or error responses, and those requests subsequently invoke DynamoDB operations. Because Actix is a Rust web framework, the risk often arises from how middleware, route handlers, or extracted state expose data that should remain scoped to the authenticated user or request context.

DynamoDB-specific exposure can happen when tokens are inadvertently included in query key expressions, conditional check attributes, or log statements that reference primary key attributes such as user_id or session_token. For example, a handler that deserializes a token into a struct field used as part of a DynamoDB key condition may leak that token in application logs or through error messages returned to downstream services. Because DynamoDB queries often include attribute values directly in request parameters, improperly sanitized inputs can expose tokens in observable request traces.

Another vector involves cross-referencing DynamoDB item attributes with request-scoped tokens. If an Actix handler retrieves an item using a user identifier derived from a token and then echoes back item metadata that includes the same token value (for instance, in a cached attribute or a misconfigured projection), the token can be reflected in API responses. This is especially relevant when using DynamoDB’s strongly consistent reads or queries that return the full item or partial attributes without proper field filtering.

In a security scan using middleBrick, such leakage would be flagged under Data Exposure and Input Validation checks, with specific reference to how token values propagate into DynamoDB request parameters and responses. The scan would highlight that tokens appearing in observable request paths or logs increase the risk of unauthorized access or replay. Remediation guidance would emphasize strict input validation, output filtering, and ensuring tokens are never stored as item attributes or used in conditional expressions.

To prevent token leakage in Actix when working with DynamoDB, isolate token handling from data access paths and ensure tokens are never part of DynamoDB keys, expressions, or logged attributes. Use dedicated identity fields that reference user or session records without embedding raw tokens.

1. Avoid including tokens in DynamoDB key expressions

Do not use authentication tokens as partition or sort key values. Instead, map tokens to opaque user identifiers before constructing requests. For example, use a hashed user ID for the partition key and keep the token out of request parameters entirely.

use aws_sdk_dynamodb::types::AttributeValue;

fn build_user_request(user_id_hash: &str, action: &str) -> aws_sdk_dynamodb::types::GetItemInput {
    aws_sdk_dynamodb::types::GetItemInput::builder()
        .table_name("UserSessions")
        .key([
            ("pk", AttributeValue::from(format!("USER#{user_id_hash}"))),
            ("sk", AttributeValue::from("METADATA")),
        ].iter().cloned().collect())
        .consistent_read(true)
        .build()
}

2. Sanitize and validate inputs before DynamoDB operations

Use strict validation for any user-supplied data that influences DynamoDB expressions. Ensure token-like values are never passed into expression attribute values used in condition checks.

fn validate_session_token(token: &str) -> Result<(), &'static str> {
    if token.len() > 256 || !token.chars().all(|c| c.is_ascii_alphanumeric() || c == '-' || c == '_') {
        return Err("invalid_token");
    }
    Ok(())
}

async fn check_session_condition(sdk_client: &aws_sdk_dynamodb::Client, token: &str) -> Result<bool, aws_sdk_dynamodb::Error> {
    validate_session_token(token)?;
    let output = sdk_client.get_item()
        .table_name("Sessions")
        .key("token_hash", AttributeValue::from(calculate_hash(token)))
        .consistent_read(true)
        .send()
        .await?;
    Ok(output.item().is_some())
}

3. Exclude sensitive fields from DynamoDB responses

When retrieving items, limit projected attributes to only those required for the operation. Avoid returning fields that could contain or reference token values. This reduces the risk of tokens being reflected in responses or logs.

fn build_limited_projection() -> aws_sdk_dynamodb::types::ScanInput {
    aws_sdk_dynamodb::types::ScanInput::builder()
        .table_name("UserProfiles")
        .projection_expression("user_id, display_name, created_at")
        .filter_expression("user_id = :uid")
        .expression_attribute_values([
            (:":uid", AttributeValue::from("known_user_id")),
        ].iter().cloned().collect())
        .build()
}

4. Isolate token handling in Actix state and middleware

Keep tokens within request-local middleware or extractor types that do not propagate into service logic that interacts with DynamoDB. Use Actix’s Data wrappers for configuration, not for runtime token storage.

struct AppState {
    client: aws_sdk_dynamodb::Client,
    // Do not store raw tokens here
}

async fn profile_handler(
    token: web::Json<AuthToken>, // Extracted and validated separately
    data: web::Data<AppState>,
) -> impl Responder {
    let user_id = hash_token(&token.value);
    let req = aws_sdk_dynamodb::types::GetItemInput::builder()
        .table_name("UserProfiles")
        .key("user_id", AttributeValue::from(user_id))
        .build();
    match data.client.get_item().set_input(Some(req)).send().await {
        Ok(out) => HttpResponse::Ok().json(out.item().unwrap_or_default()),
        Err(e) => HttpResponse::InternalServerError().body(format!("{e}")),
    }
}

5. Use DynamoDB condition expressions to enforce token-state consistency

When updating items, use condition expressions that reference non-token attributes to prevent inconsistent state updates that might expose token-related metadata.

fn build_conditional_update() -> aws_sdk_dynamodb::types::UpdateItemInput {
    aws_sdk_dynamodb::types::UpdateItemInput::builder()
        .table_name("UserSessions")
        .key("user_id", AttributeValue::from("user_hash"))
        .update_expression("SET expires_at = :new_expiry")
        .condition_expression("attribute_exists(session_id) AND version = :current_version")
        .expression_attribute_values([
            (:":new_expiry", AttributeValue::from(1717000000)),
            (:":current_version", AttributeValue::from(1)),
        ].iter().cloned().collect())
        .build()
}