Api Rate Abuse in Chi with Mongodb

Rate abuse in a Chi API backed by MongoDB occurs when an attacker sends a high volume of requests that exceed the intended request-processing limits, targeting endpoint logic that interacts with MongoDB. Chi is a functional web framework for Clojure, and its routing and middleware stack do not enforce rate limits by default. Without explicit controls, endpoints that query or write to MongoDB can be invoked repeatedly, leading to resource exhaustion, denial of service, or secondary impacts such as data exposure through error messages.

The risk is amplified when endpoints perform non-trivial operations like aggregations, lookups on large collections, or unbounded queries that consume CPU, memory, and I/O on the database side. For example, an endpoint that filters a large MongoDB collection based on user input and returns full documents can be hammered to degrade performance or to infer data presence via timing differences. Because middleBrick scans the unauthenticated attack surface, it can detect missing rate limits on Chi routes that reach MongoDB, flagging the absence of request throttling as a finding with severity and remediation guidance.

Specific attack patterns include repeated creation of records that exhaust write quotas, repeated searches that trigger expensive index scans or collection scans, and pagination endpoints with large skip values that push MongoDB into heavy cursor operations. These map to common issues in the OWASP API Top 10, such as excessive resource consumption, and can affect compliance considerations around availability and integrity. middleBrick’s rate limiting check runs in parallel with other controls, identifying whether Chi endpoints interacting with MongoDB have appropriate throttling without requiring authentication, so teams can prioritize fixes based on risk scores.

To remediate rate abuse against MongoDB in Chi, implement rate limiting at the application layer using middleware that tracks identifiers such as IP or API key, and enforce sensible query constraints on MongoDB operations. Below are concrete, realistic examples showing how to integrate rate limiting and how to adjust MongoDB interactions in Chi to reduce abuse risk.

Rate limiting with middleware

Use a rate-limiting library such as buddy or manage a token-bucket algorithm in a custom middleware. The following snippet demonstrates a simple in-memory rate limiter applied to Chi routes that hit MongoDB:

(ns myapp.routes
  (:require [compojure.core :refer [GET POST defroutes]]
            [ring.util.response :as resp]
            [buddy.core.hashers :as hashers]))

(def request-count (atom {}))

(defn rate-limit-middleware [handler]
  (fn [request]
    (let [ip (:remote-addr request)
          key (str ip (:uri request))
          current (get @request-count key 0)]
      (if (> current 100) ; allow 100 requests per evaluation window
        (resp/response "Rate limit exceeded")
        (do
          (swap! request-count assoc key (inc current))
          (handler request))))))

(defroutes app-routes
  (GET "/api/users/:id" [id] (mongodb-get-user-by-id id)) ; route backed by MongoDB
  (POST "/api/users" create-user-handler))

(def app
  (-> app-routes rate-limit-middleware)

MongoDB query safeguards

In Chi handlers, ensure MongoDB queries are bounded, use indexed fields, and avoid unbounded scans. Use projection to return only necessary fields and apply reasonable limits:

(ns myapp.db
  (:require [cheshire.core :as json]
            [monger.core :as mg])
  (def conn (mg/connect))
  (def db (mg/get-db conn "mydb")))

(defn get-users-by-query [params]
  (let [page (Integer/parseInt (get params "page" 1))
        page-size (min (Integer/parseInt (get params "pageSize" 20)) 100) ; enforce max page size
        skip (* (dec page) page-size)
        query {:status "active"}
        sort-by {:createdAt -1}]
    (with-open [cursor (.find db "users" query)
                (.skip cursor skip)
                (.limit cursor page-size)
                (.sort cursor sort-by)]
      (into [] (map json/parse-string (.toArray cursor))))))

Indexing and aggregation controls

Create appropriate indexes to ensure queries do not trigger collection scans, and place limits on aggregation pipelines to avoid expensive stages:

(ns myapp.indexes
  (:require [monger.core :as mg])
  (let [conn (mg/connect)
        db (mg/get-db conn "mydb")]
    (.ensureIndex db "users" {:email 1} {:unique true})
    (.ensureIndex db "users" {:createdAt -1})))

(defn safe-aggregation [pipeline]
  (let [max-stages 5
        capped-pipeline (take max-stages pipeline)]
    (with-open [cursor (.aggregate db "users" (to-array capped-pipeline))]
      (into [] (map #(json/parse-string % true)) (.toArray cursor)))))

By combining middleware-based throttling with disciplined MongoDB usage in Chi, teams can mitigate rate abuse while preserving availability. middleBrick’s findings can guide teams on which endpoints require rate limits and which queries need tighter constraints, supporting compliance mapping to frameworks such as OWASP API Top 10 and SOC2.