Sql Injection in Chi with Mutual Tls

SQL injection in a Chi application becomes more consequential when mutual TLS (mTLS) is used for client authentication. mTLS ensures both the client and the server present valid certificates, which strengthens transport-layer identity and access control. However, it does not change how SQL queries are built or parameterized. If the application builds SQL strings by concatenating user input, an attacker who bypasses or compromises mTLS can still inject malicious SQL through authenticated channels.

In a Chi application, routes are typically defined with parameters and middleware. When a route parameter or header value is directly interpolated into a SQL string—for example, using str concatenation or formatting functions—mTLS does not mitigate the injection risk. The mTLS handshake may confirm that the request comes from a trusted client, but it does not sanitize or validate the semantic content of that client’s data. Therefore, authenticated endpoints protected by mTLS remain vulnerable if the application logic does not treat input as untrusted.

Consider a Chi handler that retrieves a user profile using a path parameter. If the handler builds a query like "SELECT * FROM users WHERE id = '" <> id <> "'", an attacker authenticated with a valid client certificate can supply a malicious value such as 1; DROP TABLE users;. The server’s mTLS configuration will accept the connection, but the SQL string will be executed with elevated impact. This pattern is commonly associated with the OWASP API Top 10 and can map to real-world findings such as CWE-89. middleBrick’s checks for Authentication and BOLA/IDOR, when applied to a Chi API with mTLS, can surface these issues by testing authenticated attack surfaces and identifying improper input handling despite transport-layer security.

Additionally, SQL injection in Chi with mTLS can be chained with other weaknesses. For instance, if the application logs or exposes query errors, an attacker can use error-based payloads to infer schema details. Even when mTLS restricts access to known clients, insecure query construction allows unauthorized data access or modification. The scanner’s checks for Data Exposure and Input Validation complement runtime findings by highlighting unsafe string usage and missing validation, reinforcing why SQL safety must be implemented independently of transport protections.

middleBrick’s OpenAPI/Swagger analysis, including full $ref resolution, can map declared authentication schemes such as mTLS to the actual endpoints and highlight inconsistencies between documented security and runtime behavior. This is valuable for understanding how authentication mechanisms interact with business logic. By combining scan results with remediation guidance, teams can prioritize fixes that ensure user input is always treated as untrusted, regardless of transport-layer assurances.

To remediate SQL injection in a Chi application with mutual TLS, focus on safe query construction and strict input validation. mTLS should be retained for client authentication, but SQL logic must treat all inputs as untrusted. Below are concrete code examples for a Chi application that uses mTLS and a PostgreSQL client.

Example 1: Parameterized queries with next.jdbc

Use parameterized queries instead of string concatenation. This ensures user input is never interpreted as SQL code, even when a request is authenticated via mTLS.

(ns myapp.handler
  (:require [next.jdbc :as jdbc]
            [ring.util.response :as resp]))

(defn get-user [db-spec user-id]
  (jdbc/execute! db-spec ["SELECT id, email FROM users WHERE id = ?" user-id]))

(defn user-route [request]
  (let [user-id (get-in request [:params :id])
        db-spec {:dbtype "postgresql" :dbname "mydb"}]
    (if (some? user-id)
      (let [user (get-user db-spec user-id)]
        (resp/json-response user))
      (resp/bad-request "Missing user id"))))

Example 2: Using HugSQL with named parameters

HugSQL supports named parameters and enforces safe query composition. Define your SQL in a separate file and refer to it using :require.

;; resources/queries/get_user.sql
-- :name get-user :? :1
-- :doc Get a user by ID
SELECT id, email FROM users WHERE id = :id

;; handlers.clj
(ns myapp.handler
  (:require [hugsql.core :as hugsql]
            [next.jdbc :as jdbc]
            [ring.util.response :as resp]))

(hugsql/def-db-fns "resources/queries/get_user.sql")

(defn user-route [request]
  (let [db-spec {:dbtype "postgresql" :dbname "mydb"}
        user-id (get-in request [:params :id])]
    (if (and (some? user-id) (re-matches #"\d+" user-id))
      (let [user (get-user db-spec {:id user-id})]
        (resp/json-response user))
      (resp/bad-request "Invalid user id"))))

Example 3: Middleware for input validation and mTLS context

Add middleware that validates inputs and optionally inspects mTLS certificate details for logging or authorization. Keep validation independent of authentication decisions.

(ns myapp.middleware
  (:require [ring.util.response :as resp]))

(defn validate-id-param [handler]
  (fn [request]
    (let [id-param (get-in request [:params :id])]
      (if (and (some? id-param) (re-matches #"\d+" id-param))
        (handler request)
        (resp/bad-request "Invalid ID format")))))

;; Apply validation before route handler
(def app
  (-> (routes
        (GET "/users/:id" [] handler)
        ...)
      validate-id-param
      ;; mTLS is typically handled by the server or reverse proxy
      ))

Operational guidance

• Always use parameterized queries or an ORM that enforces safe SQL composition.
• Validate and sanitize all inputs, including path parameters, headers, and query strings, regardless of mTLS.
• Use tools like middleBrick to scan Chi APIs and verify that authentication schemes and input handling are correctly separated. The CLI command middlebrick scan <url> can be run against your staging endpoints to surface findings related to Authentication and Input Validation.

These practices ensure that SQL injection risks are reduced even when mTLS is in place, aligning with compliance frameworks and continuous monitoring capabilities offered by the Pro plan and GitHub Action integrations.