Sql Injection in Buffalo with Dynamodb

SQL Injection is commonly associated with relational databases, but injection-style attacks can also manifest when building queries for NoSQL stores such as DynamoDB. In a Buffalo application, if query construction builds DynamoDB API parameters (e.g., KeyConditionExpression or FilterExpression) by concatenating user input, attackers can inject expressions that change query semantics. Although DynamoDB does not execute arbitrary SQL, injection-like manipulation can bypass intended access patterns, return unintended items, or amplify data exposure.

Consider a typical lookup by user ID in a Buffalo handler that builds a DynamoDB Query request from URL parameters. If the code directly interpolates the user-supplied identifier into the KeyConditionExpression, an attacker can break out of the intended partition key scope. For example, a crafted input like user_id = '123' AND attribute_exists(aws_region) can turn a simple equality check into a condition that matches more items or changes the filtering behavior, potentially exposing other users’ data when insufficient authorization checks are present.

Because middleBrick scans the unauthenticated attack surface and tests input validation and authorization, such expressions are surfaced as findings. The scanner does not assume a relational database; it flags injection-like risks where user-controlled input influences query structure. These findings map to the OWASP API Top 10 (e.g., Broken Object Level Authorization and Injection) and can be tied to compliance frameworks such as SOC2 and GDPR, emphasizing the need for strict input validation and authorization regardless of the database backend.

When scanning a Buffalo endpoint that interacts with DynamoDB, middleBrick’s checks—particularly Input Validation, Property Authorization, and BOLA/IDOR—help detect whether expressions are constructed safely. The scanner’s OpenAPI/Swagger analysis cross-references defined parameters with runtime behavior to highlight mismatches where user input reaches query-building logic without adequate sanitization or contextual validation.

Remediation centers on never directly concatenating user input into DynamoDB expressions and instead using language-level mechanisms for constructing safe queries. In Elixir with the AWS SDK for DynamoDB, prefer strongly typed structures and parameterized approaches where possible. Always validate and sanitize inputs, enforce ownership checks, and use condition expressions conservatively.

Below is a vulnerable Buffalo handler that builds a KeyConditionExpression by string interpolation:

defmodule ExampleController do
  use ExampleController, :controller

  def show(conn, %{"user_id" => user_id}) do
    key_condition = "user_id = '#{user_id}'"
    filter = "status = 'active'"

    dynamo = MyApp.DynamoClient.query(
      table_name: "users",
      key_condition_expression: key_condition,
      filter_expression: filter
    )

    json(conn, dynamo)
  end
end

An attacker can manipulate user_id to alter the query logic. A safer approach uses explicit parameterization and validation. For DynamoDB, there is no native prepared-statement mechanism like SQL, so you must ensure that injected values are treated strictly as data. One pattern is to validate the format of IDs and construct the expression using a controlled function that only permits safe values:

defmodule ExampleController do
  use ExampleController, :controller

  def show(conn, %{"user_id" => user_id}) do
    with {:ok, safe_id} <- validate_user_id(user_id),
         {:ok, query} <- build_query(safe_id) do
      dynamo = MyApp.DynamoClient.query(
        table_name: "users",
        key_condition_expression: query.key_condition,
        filter_expression: query.filter
      )
      json(conn, dynamo)
    else
      {:error, :invalid_input} -> send_resp(conn, 400, "Invalid user ID")
    end
  end

  defp validate_user_id(id) when id =~ ~r/^u[a-f0-9-]{36}$/, do: {:ok, id}
  defp validate_user_id(_), do: {:error, :invalid_input}

  defp build_query(user_id) do
    # Use explicit expression attribute values to keep data separate from expression structure
    key_condition = "user_id = :uid"
    filter = "status = :active"

    expression_attribute_values = %{
      ":uid" => %{"S" => user_id},
      ":active" => %{"S" => "active"}
    }

    {:ok, %{key_condition: key_condition, filter: filter, expression_attribute_values: expression_attribute_values}}
  end
end

This approach ensures that user input never becomes part of the expression structure. By using expression attribute values, you separate data from the query syntax, which DynamoDB treats as placeholders rather than executable code. Additionally, enforce server-side authorization to confirm that the requesting user is allowed to access the requested resource, mitigating BOLA/IDOR risks even when input is well-formed.

For broader protection in CI/CD, the middleBrick Pro plan includes continuous monitoring and GitHub Action integration to fail builds if security thresholds are not met. This helps catch regressions where unsafe query patterns might re-enter the codebase. Developers can also integrate middleBrick directly from their IDE using the MCP Server to scan DynamoDB-related endpoints during development.