Buffer Overflow in Chi with Dynamodb

A buffer overflow in a Chi application that interacts with DynamoDB typically arises when unbounded or untrusted input is used to construct low-level buffers passed to system calls or native extensions, while DynamoDB usage influences what data is processed, stored, and retrieved. For example, if a Chi handler deserializes a DynamoDB record into a fixed-size binary buffer without length validation, an attacker can supply a record with an unexpectedly large attribute value that overflows the buffer. This can corrupt stack memory, overwrite return addresses, or lead to arbitrary code execution depending on runtime protections.

DynamoDB-specific factors that can expose or worsen the risk include:

• Large attribute values or unbounded lists/maps returned by queries or scans that are not validated before being copied into constrained buffers.
• Deserialization logic that assumes size limits enforced by DynamoDB, which an attacker can bypass by directly injecting crafted payloads if the data is later used in native operations (e.g., via NIFs or ports).
• Inadvertent concatenation or reconstruction of data from multiple DynamoDB items into a single buffer, increasing the effective input size beyond safe thresholds.

Because middleBrick tests input validation and unsafe consumption as part of its 12 checks, it can surface these classes of flaws in unauthenticated scans, highlighting risky patterns in how DynamoDB responses are handled by Chi before they are processed or forwarded.

Remediation focuses on strict input validation, bounded binaries, and safe data handling when working with DynamoDB records in Chi. Always treat data from DynamoDB as untrusted and enforce size limits before copying into fixed-size structures.

1. Validate and bound DynamoDB attribute sizes

Before using binary or string attributes from DynamoDB, check their length and reject or truncate them to a safe maximum.

defmodule MyApp.Handler do
  @max_payload 8192

  def handle_dynamo_item(item) do
    with {:ok, %{payload: payload}} <- Map.fetch(item, "payload"),
         {:ok, bounded} <- bound_binary(payload, @max_payload) do
      # safe to use bounded binary in further processing
      process(bounded)
    else
      :error -> {:error, :invalid_payload}
    end
  end

  defp bound_binary(value, max) when byte_size(value) <= max, do: {:ok, value}
  defp bound_binary(_value, _max), do: {:error, :too_large}
end

2. Use Ecto-like schemas and casting for DynamoDB records

Define explicit schemas for your DynamoDB-derived data and cast/validate each field to prevent oversized or malicious values from flowing into buffers or native ports.

defmodule MyApp.Schema do
  @max_name 255

  defstruct [:id, :name, :data]

  def cast(item) do
    with {:ok, id} <- validate_id(item["id"]),
         {:ok, name} <- validate_string(item["name"], @max_name),
         {:ok, data} <- validate_binary(item["data"], 4096) do
      {:ok, %__MODULE__{id: id, name: name, data: data}}
    else
      _ -> :error
    end
  end

  defp validate_id(v), when is_binary(v) and byte_size(v) <= 1024, do: {:ok, v}
  defp validate_id(_), do: :error

  defp validate_string(v, max) when is_binary(v) and byte_size(v) <= max, do: {:ok, v}
  defp validate_string(_, _), do: :error

  defp validate_binary(v, max) when is_binary(v) and byte_size(v) <= max, do: {:ok, v}
  defp validate_binary(_, _), do: :error
end

3. Avoid concatenating multiple DynamoDB records into a single buffer

If your Chi logic merges several DynamoDB items into one binary blob, enforce per-item and total size caps, and process streams incrementally rather than building large in-memory buffers.

defmodule MyApp.StreamedConsumer do
  def consume(enumerable, acc \\ <<>>, limit \\ 65_536)

  def consume([], acc, _limit) when byte_size(acc) <= limit, do: {:ok, acc}
  def consume([], _acc, _limit), do: :error

  def consume([item | rest], acc, limit) do
    case Map.fetch(item, :chunk) do
      {:ok, chunk} when byte_size(chunk) > 0 ->
        if byte_size(acc) + byte_size(chunk) <= limit do
          consume(rest, <>, limit)
        else
          :error
        end
      _ ->
        :error
    end
  end
end

By combining these patterns with middleBrick scans, you can detect missing length checks and unsafe consumption patterns in your Chi + DynamoDB stack and address them before attackers can exploit them.