Brute Force Attack in Chi with Dynamodb

A brute force attack against a Chi application using Amazon DynamoDB typically arises when authentication or session tokens are validated without sufficient rate limiting or account lockout mechanisms. In this scenario, an attacker can systematically guess credentials or token values and send requests directly to backend endpoints that query DynamoDB to verify identity.

Because DynamoDB is often used as a high-throughput datastore for user data, a vulnerable Chi route that looks up items by username or user ID can be probed repeatedly without throttling. For example, a login route implemented in Chi might parse a JSON body, forward the username to a DynamoDB getItem call, and then compare a hashed password. If this route does not enforce request-rate limits or progressive delays after failed attempts, an attacker can iterate over password guesses or session identifiers quickly.

The unauthenticated attack surface exposed by such routes is exactly what middleBrick’s 12 security checks evaluate in parallel, including Authentication, Rate Limiting, and BOLA/IDOR testing. A scan can detect whether responses differ meaningfully between valid and invalid users, and whether the endpoint lacks protections like exponential backoff or captchas. Without these controls, brute force attempts can consume server resources and potentially lead to unauthorized access, data exposure, or exhaustion of provisioned read capacity in DynamoDB.

middleBrick scans identify these risks by sending sequential probes and analyzing response codes, timing variance, and error messages. If a Chi endpoint returns predictable success/failure indicators and does not enforce global rate limits, the scan flags the Authentication and Rate Limiting checks with severity findings and remediation guidance. This helps teams understand how an attacker might chain brute force techniques with DynamoDB queries to compromise accounts.

To mitigate brute force risks in a Chi application using DynamoDB, implement rate limiting at the router level and ensure that authentication logic does not reveal useful information to unauthenticated callers. Below are concrete code examples that demonstrate these protections.

Rate limiting in Chi

Use a middleware that tracks request counts per key (e.g., IP or API key) and enforces a maximum number of requests per window. Here is an example using the liberator library, which integrates cleanly with Chi routes:

(ns myapp.middleware
  (:require [liberator.middleware :refer [rate-limit]]))

(defn wrap-rate-limiting [handler]
  (rate-limit handler {:limit 30
                       :window 60
                       :on-exceeded #(do (-> % :response (assoc :status 429 :body "Too Many Requests")))}))

Then apply this middleware to your authentication route:

(defroutes app-routes
  (POST "/login" [] login-handler))

(def app
  (-> app-routes
      wrap-rate-limiting
      wrap-key-params)) ; if you parse JSON body as keywords

Secure DynamoDB lookup pattern

Ensure that your DynamoDB queries do not leak information via timing differences or distinct HTTP status codes. Use a constant-time comparison for password checks and return a generic response for invalid users. Example using the official AWS SDK for Clojure (v2):

(ns myapp.auth
  (:require [aws.sdk.dynamodb :as ddb]))

(defn get-user-by-username [client username]
  (let [resp (ddb/get-item client
                           {:table-name "users"
                            :key {"username" {:s username}}})]
    (:item resp)))

(defn verify-password [stored-hash candidate)
  ;; Use a constant-time comparison to avoid timing leaks
  (security/check-eq stored-hash (hash candidate)))

(defn login-handler [request]
  (let [username (get-in request [:body-params :username])
        candidate (get-in request [:body-params :password])
        user (get-user-by-username ddb-client username)]
    (if (and user (verify-password (:password-hash user) candidate))
      {:status 200 :body {:token (str (random-uuid))}}
      {:status 200 :body {:token nil}}))) ; always 200 to avoid user enumeration

Additionally, enable DynamoDB auto scaling or provisioned capacity with burst capacity to reduce the impact of sustained probes on read throughput. Combine these measures with the findings and remediation steps provided by a middleBrick scan to validate that Authentication, Rate Limiting, and BOLA/IDOR checks reach an acceptable risk level.