Insecure Deserialization in Chi with Mongodb

Insecure deserialization occurs when an application accepts and processes serialized data without validating its integrity or origin. In a Chi application that uses Mongodb as a persistence layer, this typically happens when endpoint parameters or request bodies are deserialized and then used to construct database queries. For example, if a Chi route deserializes a JSON or BSON payload via cheshire3 or a custom deserializer and directly passes values into a Mongodb query, attacker-controlled data can influence query structure or command execution. This becomes particularly dangerous when the deserialization process is too permissive or when the application trusts data stored in Mongodb without re-validation.

Chi routes are often defined as functions that destructure parameters and query maps; if a developer uses get-in or similar to extract a user-supplied value and then builds a Mongodb filter with that value, they may inadvertently allow injection-like behavior through malformed or malicious serialized inputs. While Chi itself does not perform deserialization, the surrounding ecosystem—such as libraries that decode JSON or BSON into Clojure data structures—can introduce risks if they do not enforce strict schemas. Attackers may craft payloads that exploit edge cases in those libraries to achieve remote code execution or unauthorized data access when the resulting data is later used in Mongodb operations.

Additionally, if an API exposes endpoints that return Mongodb documents directly or include internal fields such as _id or metadata, an attacker might manipulate references to trigger insecure deserialization on the server side when those references are reconstructed. This is relevant when combined with other findings such as Property Authorization or BOLA/IDOR, as the deserialized data may bypass intended access controls. Because middleBrick tests unauthenticated attack surfaces, it can detect endpoints where deserialization-related inputs reach the database layer without proper validation, highlighting risks tied to data exposure and injection in the context of Mongodb interactions.

To secure a Chi application using Mongodb, enforce strict input validation and avoid direct deserialization of untrusted data into database queries. Use schema-aware libraries such as Malli or Spec to validate incoming payloads before they are transformed into Mongodb operations. Always construct queries using explicit, parameterized conditions rather than dynamically merging maps that may originate from serialized inputs.

Below are concrete Mongodb examples for Chi that demonstrate safe practices. First, define a validation schema using Malli and integrate it into your route handler:

(ns secure-api.routes
  (:require [cheshire.core :as json]
            [malli.core :as m]
            [malli.util :as mu]
            [monger.core :as mg]
            [monger.collection :as mc]))

(def user-params-schema
  [:map
   [:user-id :string]
   [:action [:enum ["read" "write" "delete"]]]])

(defn validate-params [params]
  (if (m/validate user-params-schema params)
    (mu/dissoc-in params [:password]) ; remove sensitive fields if present
    (throw (ex-info "Invalid parameters" {:status 400}))))

(defn handle-get [request]
  (let [params (-> request :params validate-params)
        user-id (:user-id params)
        conn (mg/connect)
        db (mg/get-db conn "appdb")
        document (mc/find-maps db :users {:user-id user-id})]
    {:status 200
     :body (json/generate-string document)}))

In this example, incoming query parameters are validated against a strict schema before being used in a Mongodb query. The validate-params function ensures that only expected keys and value types reach the database layer. The query itself uses a direct filter map with a known-safe key (:user-id) rather than merging untrusted deserialized data, preventing injection-style manipulation through malformed inputs.

Second, when updating documents, explicitly specify allowed fields and avoid passing raw deserialized maps:

(def update-schema
  [:map
   [:status [:enum ["active" "inactive"]]]
   [:updated-at :inst?]])

(defn safe-update-user [request]
  (let [params (-> request :params validate-params)
        conn (mg/connect)
        db (mg/get-db conn "appdb")
        result (mc/update-by-id db (:user-id params)
                                {:$set {:status (:status params)
                                        :updated-at (java.util.Date.)}})
        updated (mc/find-maps db :users {:user-id (:user-id params)})]
    {:status 200
     :body (json/generate-string updated)})

Here, the update operation uses explicit field names rather than dynamically constructing a $set document from untrusted input. This approach aligns with remediation guidance provided by middleBrick findings, especially under Property Authorization and Input Validation checks. By combining schema validation with explicit query construction, you reduce the risk that deserialization-related issues will propagate to the Mongodb layer.

Finally, ensure that any serialization formats used in logging, caching, or inter-service communication do not inadvertently expose internal Mongodb identifiers or structures. Prefer canonical representations and avoid embedding raw _id values in URLs or client-facing payloads without proper encoding and validation.