Api Key Exposure in Chi with Postgresql

Chi is a functional programming language for the JVM that often interoperates with PostgreSQL for data persistence. When API keys are handled in Chi services that connect to PostgreSQL, exposure can occur through insecure coding patterns, runtime leaks, or insufficient access controls. Unlike compiled languages with strict type-driven safety, Chi’s dynamic nature and macros can inadvertently propagate sensitive values into logs, error messages, or responses if the developer does not enforce strict scoping and sanitization.

PostgreSQL itself does not store Chi API keys, but the application layer typically holds keys in configuration, environment variables, or connection strings that the Chi runtime accesses. If a Chi application embeds keys directly in queries, constructs dynamic SQL via string interpolation, or uses improper logging, an attacker who gains SQL or application access can harvest these keys. Common vectors include:

• Logging full request or response payloads that contain authorization tokens generated by Chi services.
• Returning stack traces or internal errors that expose variables in scope, including key material passed to PostgreSQL functions or drivers.
• Misconfigured connection strings stored in environment variables that are readable by non-privileged processes or exposed through debug endpoints.

The combination increases risk because Chi code may pass sensitive values to PostgreSQL extensions or user-defined functions (e.g., via JDBC or HTTP interfaces) without redaction. For example, a Chi handler that builds a query using concatenation can leak keys if an error reveals the constructed statement. An attacker performing black-box scanning with middleBrick can detect this by probing unauthenticated endpoints that interact with PostgreSQL and analyzing responses for patterns indicative of key exposure, such as tokens appearing in JSON fields or verbose errors.

middleBrick’s LLM/AI Security checks are particularly effective at identifying prompt or key leakage in Chi services that expose language model endpoints, but for PostgreSQL-facing APIs, it focuses on input validation, data exposure, and unsafe consumption checks. By scanning the unauthenticated attack surface in 5–15 seconds, middleBrick can surface findings like missing input sanitization or excessive data reflection that facilitate key extraction.

Remediation guidance centers on treating API keys as secrets never to appear in logs, queries, or client-side artifacts. In Chi, prefer read-only references to keys stored in secure configuration providers, and ensure any data sent to PostgreSQL is parameterized. middleBrick’s dashboard and CLI reports map findings to frameworks like OWASP API Top 10 and provide prioritized remediation steps, helping teams break the chain from Chi code to exposed credentials.

Secure integration between Chi and PostgreSQL requires disciplined handling of API keys and query construction. Below are concrete, realistic code examples that demonstrate how to mitigate exposure in a Chi service.

1. Use environment variables and a secure configuration reader, never hardcode keys. In Chi, leverage libraries that provide immutable configuration access without runtime reflection that could expose values.

;; chi-app/config.chi
(import [java.util Base64])

(defn get-env [k]
  (or (System/getenv k)
      (throw (Exception. (str "Missing env var: " k)))))

(def db-url (get-env "DB_URL"))
(def api-key (get-env "API_KEY"))

2. Parameterize all SQL statements to prevent injection and avoid string interpolation that can leak keys in error messages. Use prepared statements via JDBC or a type-safe wrapper; never concatenate user input into queries.

;; chi-app/db.clj
(import '[java.sql DriverManager PreparedStatement])

(defn with-conn [f]
  (let [conn (DriverManager/getConnection db-url api-key)]
    (try
      (f conn)
      (finally (.close conn)))))

(defn get-user [user-id]
  (with-conn (fn [conn]
    (let [stmt (.prepareStatement conn "SELECT id, name FROM users WHERE id = ?")]
      (.setString stmt 1 user-id)
      (with-open [rs (.executeQuery stmt)]
        (when (.next rs)
          {:id (.getString rs "id")
           :name (.getString rs "name")})))))

3. Redact sensitive values in logging and error handling. Ensure that any log line or exception message never includes the API key, even for debugging. In Chi, wrap key usage with functions that strip or mask secrets before output.

;; chi-app/logging.clj
(defn safe-log-query [query params]
  (let [masked-params (map (fn [p] (if (string? p) "**REDACTED**" p)) params)]
    (println (str "[QUERY] " query " | params: " masked-params))))

;; Usage in a handler
(try
  (safe-log-query "SELECT * FROM tokens WHERE user_id = ?" [user-id])
  (get-user user-id)
  (catch Exception e
    (println (str "[ERROR] Request failed: " (.getMessage e)))))

4. Restrict PostgreSQL permissions for the Chi application role to the minimum required. Create a dedicated database role that cannot view system catalogs or other users’ data, limiting the impact of a potential key exposure.

-- PostgreSQL setup (run once via psql)
CREATE ROLE chi_app WITH LOGIN PASSWORD 'strong-password';
GRANT CONNECT ON DATABASE mydb TO chi_app;
GRANT USAGE ON SCHEMA public TO chi_app;
GRANT SELECT, INSERT, UPDATE ON TABLE users, tokens TO chi_app;
REVOKE ALL ON DATABASE mydb FROM PUBLIC;

5. Rotate keys and monitor for anomalies. Even with safe code, treat keys as short-lived. Integrate with middleBrick’s continuous monitoring (Pro plan) to detect unusual query patterns or access attempts that suggest key compromise.

By combining secure configuration, parameterized queries, strict logging discipline, and least-privilege database roles, Chi applications can interact with PostgreSQL without exposing API keys. middleBrick scans validate these practices by identifying input validation gaps, data exposure risks, and unsafe consumption patterns, enabling teams to remediate before an attacker exfiltrates credentials.