Sql Injection in Chi with Jwt Tokens

SQL injection in a Chi application that uses JWT tokens can occur when token payloads or claims are improperly incorporated into SQL queries. Chi is a routing library for Clojure that encourages explicit parameter handling, but developers may still construct dynamic SQL using values derived from request context, such as custom middleware that adds claims from a JWT to the request map.

For example, if a route handler reads a user identifier from a JWT claim and uses string concatenation or naive interpolation to build a query, the application becomes vulnerable. Consider a handler that builds a SQL statement like "SELECT * FROM users WHERE org_id = " ++ org-id, where org-id originates from the JWT claim :org_id. An attacker who can influence the token—through account takeover, token leakage, or a downstream system that embeds attacker-controlled data into the token—can inject malicious SQL such as 1 OR 1=1, leading to unauthorized data access or modification.

In Chi, this risk is amplified when JWT validation is performed by a separate service or library and the decoded claims are treated as trusted. Even if the token is cryptographically verified, claims may not be safe for direct use in SQL. Attack patterns such as Authentication Bypass or Insecure Direct Object Reference (BOLA/IDOR) can intersect with SQL injection if the token identifies a resource (e.g., tenant or user) that the query uses without additional authorization checks.

Middleware that injects JWT-derived values into SQL strings bypasses the safety of parameterized queries. Chi encourages composability, but if developers compose SQL via string functions or macros that do not enforce parameterization, the attack surface remains open. Data exposure and improper validation checks may flag this in a middleBrick scan, especially when the scanner sends payloads like ' OR 1=1 -- through parameters that ultimately reach SQL code built from JWT claims.

Without runtime analysis that correlates JWT usage with SQL construction, such vulnerabilities can remain undetected. middleBrick’s checks for input validation and property authorization help surface these risks by testing how user-influenced data, including token claims, is handled across the unauthenticated attack surface.

Remediation centers on strict separation between token validation and data access, using parameterized queries and explicit claim validation. Never concatenate or interpolate JWT claims into SQL strings.

Use Clojure’s next.jdbc with prepared statements. For example, given a JWT that contains a user ID, extract and validate the claim, then pass it as a parameter:

(require '[next.jdbc :as jdbc]
         '[cheshire.core :as json])

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

In a Chi handler, ensure the claim is parsed and validated before use:

(defn authenticated-handler [request]
  (let [claims (:claims request) ; assume claims already validated by middleware
        org-id (:org_id claims)]
    (when (integer? org-id)
      (get-user-by-org *db* org-id))))

For JWT validation, use a well-audited library such as buddy. Do not trust the token payload for authorization decisions without rechecking against a data store:

(require '[buddy.auth.backends.token :as token])

(def jwt-backend (token/jws {:alg :hs256}))

(defn verify-token [token-string]
  (try
    (token/verify token-string jwt-backend {:check-expiration true})
    (catch Exception _
      nil)))

Apply principle of least privilege: scope database permissions to the minimum required operations, and enforce row-level security in the database for tenant-specific data. Combine these practices with continuous scanning using tools like middleBrick’s Pro plan, which provides GitHub Action integration to fail builds if risk scores degrade and offers CLI scanning from the terminal with JSON output for automation.

Finally, treat JWTs as opaque identifiers for authentication and keep authorization logic server-side, validating each request against canonical sources rather than relying on token-embedded claims for SQL construction.