Brute Force Attack in Rocket with Dynamodb

A brute force attack against a Rocket API backed by DynamoDB typically arises when authentication or authorization is enforced at the application layer rather than being handled by a dedicated identity provider. In this setup, each login or token validation request results in one or more DynamoDB queries—often to retrieve user records, to check credentials, or to validate multi-factor tokens. If these endpoints do not implement strict rate limiting or adaptive throttling, an attacker can send many rapid guesses against usernames and passwords, or iterate over possible one-time codes, causing the Rocket service to issue repeated DynamoDB read operations.

The exposure is amplified because DynamoDB queries are relatively fast at low scale, which allows an attacker to perform many attempts within a short window. In a black-box scan, middleBrick’s authentication and rate-limiting checks will flag endpoints where credential verification triggers repeated unauthenticated DynamoDB calls without progressive delays or lockouts. Attack patterns such as credential stuffing or token enumeration map to the OWASP API Top 10 category for Broken Authentication and can align with real-world findings similar to CVE-2021-24086, where weak account lockout policies enable online password guessing.

When OpenAPI specs describe these endpoints without explicit security schemes or rate-limit metadata, middleBrick’s spec analysis correlates the runtime behavior with defined paths and identifies where DynamoDB operations are invoked per request. The scanner does not inspect internal code but detects that unauthenticated or insufficiently throttled endpoints permit high-frequency queries to DynamoDB, which is a precursor to successful brute force attempts. This is why middleBrick’s Authentication and Rate Limiting checks are valuable: they highlight the absence of safeguards that would otherwise slow down or block iterative guessing.

In a typical Rocket route, a naive implementation might query DynamoDB on every login attempt to load a user by a username provided directly from the request. If the route does not enforce per-identifier delays or global request caps, the route effectively becomes a brute force vector. MiddleBrick’s findings will show missing controls such as exponential backoff hints or explicit account lockout guidance, emphasizing the need to move credential validation away from direct DynamoDB lookups under high-frequency scenarios.

To mitigate brute force risks, reduce the number of DynamoDB calls per authentication attempt and enforce strict rate controls at the Rocket route level. Prefer a design where a lightweight cache or a dedicated identity service handles credential verification, and DynamoDB is used only after successful authentication for profile data. Below are concrete examples using the official AWS SDK for Rust within a Rocket handler.

First, configure a rate limiter using a token-bucket approach that applies per username or per IP before any DynamoDB interaction. This ensures that even if the attacker knows valid usernames, the effective requests per second are capped.

use rocket::State;
use std::sync::Arc;
use aws_sdk_dynamodb::Client;
use std::time::{Duration, Instant};

struct RateLimiter {
    last_attempts: std::collections::HashMap,
    min_interval: Duration,
}

impl RateLimiter {
    fn new(min_interval: Duration) -> Self {
        Self {
            last_attempts: std::collections::HashMap::new(),
            min_interval,
        }
    }

    fn allow(&mut self, key: &str) -> bool {
        let now = Instant::now();
        let should_allow = self.last_attempts
            .get(key)
            .map(|prev| now.duration_since(*prev) >= self.min_interval)
            .unwrap_or(true);
        if should_allow {
            self.last_attempts.insert(key.to_string(), now);
        }
        should_allow
    }
}

#[rocket::post("/login", data = <user>)]
async fn login(
    user: rocket::serde::json::Json<LoginRequest>,
    dynamodb: &State<Arc<Client>>,
    limiter: &State<Arc<tokio::sync::Mutex<RateLimiter>>>
) -> rocket::response::status::Status {
    let key = format!("login:{}", user.username);
    let mut limiter = limiter.lock().await;
    if !limiter.allow(&key) {
        return rocket::http::Status::TooManyRequests;
    }
    // After rate check, proceed with minimal DynamoDB calls
    let resp = dynamodb
        .get_item()
        .table_name("users")
        .key("username", aws_sdk_dynamodb::types::AttributeValue::S(user.username.clone()))
        .send()
        .await;
    // Validate credentials and return appropriate status
    rocket::http::Status::Ok
}

Second, use DynamoDB conditional writes or update expressions for any lockout metadata rather than performing multiple separate reads. For example, maintain a failed_attempts attribute and update it atomically:

use aws_sdk_dynamodb::types::UpdateExpression;

async fn record_failure(
    client: &Client,
    username: &str
) -> Result<(), aws_sdk_dynamodb::Error> {
    client.update_item()
        .table_name("users")
        .key("username", aws_sdk_dynamodb::types::AttributeValue::S(username.to_string()))
        .update_expression("SET failed_attempts = if_not_exists(failed_attempts, :zero) + :inc")
        .expression_attribute_values(":inc", aws_sdk_dynamodb::types::AttributeValue::N("1".to_string()))
        .expression_attribute_values(":zero", aws_sdk_dynamodb::types::AttributeValue::N("0".to_string()))
        .send()
        .await?;
    Ok(())
}

Third, enforce account lockout or progressive delays based on the attribute stored in DynamoDB. Only after these checks should sensitive operations proceed. These patterns reduce the number of DynamoDB operations per authentication cycle and ensure that brute force attempts are throttled regardless of attacker knowledge of the backend.