Integrity Failures in Chi with Dynamodb

Integrity failures occur when an API allows unauthorized modification, deletion, or corruption of data. In a Chi application using Amazon DynamoDB as the persistence layer, this typically arises from missing or bypassed authorization checks on data access paths. Chi routes are often defined as a series of handlers, and if a route that performs a UpdateItem or DeleteItem does not validate that the authenticated subject owns or is permitted to act on the target resource, an attacker can manipulate identifiers to access or mutate other users' data.

DynamoDB relies on primary keys (partition key, and optionally sort key) to uniquely identify items. In Chi, it is common to extract identifier values from route parameters (e.g., /users/:userId) and use them directly in DynamoDB API calls. If the application does not enforce ownership or scope checks—such as ensuring that the userId in the route matches the user’s identity from the session or token—an attacker can change the parameter to access or modify another user’s item. This is a classic Broken Level of Authorization (BOLA) / Insecure Direct Object Reference (IDOR) pattern that maps directly to the OWASP API Top 10 and appears in many PCI-DSS and SOC2 control mappings.

Because DynamoDB is a NoSQL store, integrity risks also emerge from partial updates and conditional writes. A Chi handler that performs an update without verifying the current state or without using a conditional expression can overwrite concurrent changes, leading to data corruption. For example, if two requests attempt to update a user’s profile or financial balance without an atomic compare-and-set guard, the last write may silently discard the other, violating integrity. In distributed systems, this is sometimes referred to as a lost update. The absence of optimistic locking via ConditionExpression with attribute existence checks or version attributes (e.g., a numeric version or timestamp) is a common root cause.

Another DynamoDB-specific integrity concern involves malformed or missing key schemas in item representations. If a Chi service constructs DynamoDB AttributeValue maps manually or via a library without strict type validation, it may accept malformed inputs that produce unexpected item states. For instance, representing a numeric balance as a string instead of a number can cause comparison and arithmetic operations to behave incorrectly downstream, leading to integrity violations at the application level. Input validation coupled with schema-aware parsing is essential to prevent injection of invalid data shapes that DynamoDB will accept but your domain logic cannot safely consume.

When scanning such an API with middleBrick, these integrity issues surface in the BOLA/IDOR and Property Authorization checks, alongside Input Validation. The scanner cross-references the OpenAPI specification—where path parameters and expected payload shapes are defined—against runtime behavior to detect missing authorization or missing conditional checks. Findings include severity ratings and remediation guidance that map to frameworks like OWASP API Top 10 and compliance regimes. For teams using the middleBrick Pro plan, continuous monitoring can be configured to detect regressions in integrity controls, and the GitHub Action can fail a build if a scan drops below a defined security score threshold.

Remediation focuses on enforcing ownership, using conditional writes, and validating data shapes before they are marshaled into DynamoDB AttributeValue structures. Below are concrete code examples for Chi handlers that demonstrate these patterns. These examples assume you are using the official AWS SDK for JavaScript/Node.js and a typical Chi route definition.

1. Enforce ownership with BOLA checks

Ensure that any operation on a resource verifies that the resource’s owner matches the authenticated subject. This prevents IDOR by design.

// routes/users.cljs (or .cljc)
(defn update-user-handler [request]
  (let [user-id (get-in request [:params :route-params :user-id])
        subject-id (:user-id request) ; authenticated identity from session/token
        db-client (get-in request [:middleware/db])
        ; 1) Fetch the item to confirm ownership
        item (dynamodb/get-item db-client {:table-name "users"
                                           :key {"id" {:s user-id}}})]
    (if (not= (:user-id item) subject-id)
      {:status 403 :body "Forbidden"}
      (let ; 2) Proceed with update using a ConditionExpression to prevent lost updates
        (dynamodb/update-item db-client
          {:table-name "users"
           :key {"id" {:s user-id}}
           :update-expression "set profile = :p, version = version + :inc"
           :condition-expression "attribute_exists(id) AND version = :expected_version"
           :expression-attribute-values {":p" (marshall-profile (:body request))
                                        ":inc" {:n "1"}
                                        ":expected_version" {:n (str (:version item))}}
           :return-values "ALL_NEW"})
        {:status 200 :body "ok"})))

2. Use conditional writes for balance and state integrity

When modifying mutable state such as balances or counters, use DynamoDB’s conditional expressions to implement optimistic locking. This ensures that concurrent updates do not corrupt data.

;; Update balance safely with a condition that the balance does not go negative
(dynamodb/update-item db-client
  {:table-name "accounts"
   :key {"accountId" {:s "acc-123"}}
   :update-expression "set balance = balance - :amount"
   :condition-expression "balance >= :min_balance"
   :expression-attribute-values {":amount" {:n "50.00"}
                                ":min_balance" {:n "0"}}})
;; Handle ConditionalCheckFailedException in your client code to retry or report a conflict.

3. Validate and shape input before marshalling

Never pass raw user input directly into DynamoDB attribute maps. Validate types and shapes to avoid corrupting item schemas.

(defn validate-and-marshal [input]
  (when-not (string? (:user-id input))
    (throw (ex-info "Invalid user-id" {:type ::invalid-type})))
  (when-not (number? (:balance input))
    (throw (ex-info "Balance must be a number" {:type ::invalid-type})))
  ; safe to marshal
  {"userId" {:s (:user-id input)}
   "balance" {:n (str (:balance input))}
   "email" {:s (:email input)}})

;; In a handler:
(let [validated (validate-and-marshal (:body request))
      put-result (dynamodb/put-item {:table-name "users" :item validated})]
  {:status 201 :body "created"})

4. Prefer TransactWriteItems for atomic multi-item updates

When operations must affect multiple items, use a transaction to preserve consistency. This avoids partial writes that can leave the dataset in an invalid state.

(dynamodb/transact-write-items db-client
  {:transact-items [{:update {:table-name "ledger"
                              :key {"id" {:s "ledger-001"}}
                              :update-expression "set amount = amount - :v"
                              :expression-attribute-values {":v" {:n "100"}}}}
                     {:update {:table-name "balances"
                               :key {"userId" {:s "user-abc"}}
                               :update-expression "set amount = amount + :v"
                               :expression-attribute-values {":v" {:n "100"}}}}]
   :condition-expression "ledger.amount >= :v"
   :expression-attribute-values {":v" {:n "100"}}})

By combining ownership validation, conditional expressions, strict input validation, and transactional writes, Chi applications using DynamoDB can maintain data integrity even under concurrent or malicious traffic. middleBrick scans help surface missing checks by comparing declared routes and schemas against observed behavior, and the remediation guidance aligns with best practices for OWASP API Top 10 and common compliance requirements.