Api Rate Abuse in Phoenix with Cockroachdb

Rate abuse in a Phoenix API backed by CockroachDB arises because application-level rate limiting is enforced after requests reach the Phoenix endpoint, while CockroachDB’s strong consistency and distributed nature can amplify the impact of uncontrolled request volume. Without a boundary at the edge or within Phoenix, an authenticated or unauthenticated attacker can issue many legitimate-looking queries that drive high read or write throughput on CockroachDB nodes. CockroachDB handles concurrency with serializable isolation, which means long-running or high-rate transactions can increase contention, cause transaction retries, and degrade latency for legitimate users. Because Phoenix applications often expose CRUD endpoints that map directly to CockroachDB tables, missing or weak rate limits on these endpoints allow attackers to exhaust connection pools, drive CPU usage on database nodes, or trigger noisy neighbor effects in shared clusters. This combination does not introduce new database-side vulnerabilities, but it exposes operational risk: without request throttling at the API layer, CockroachDB’s resilience features can be turned against itself as sustained load leads to timeouts, elevated latencies, and potential degradation of service. The risk is especially acute for endpoints that perform writes or indexed lookups on high-cardinality columns, since CockroachDB must coordinate across ranges and these operations consume more resources per request. In a typical Phoenix stack using Ecto with the CockroachDB Postgres wire protocol, each unchecked request results in a database transaction; if rate limiting is omitted, an attacker can generate many transactions that compete for row locks or cause schema-related contention on system tables. Effective mitigation requires applying rate limits before requests invoke Ecto queries, ensuring that CockroachDB only processes traffic the system is designed to handle.

Remediation focuses on enforcing request-rate boundaries in Phoenix before queries reach CockroachDB, and designing database interactions to be resilient under load. Use pluggable rate-limiting strategies such as token-bucket or sliding-window counters stored in a shared, low-latency store. Because CockroachDB excels at consistency but is not an in-memory store, avoid using it as the primary rate-limiting backend; instead, use Redis or Memcached with Phoenix and Ecto to track request counts per key. The following patterns demonstrate how to implement rate limiting in a Phoenix API that uses Ecto with CockroachDB.

1. Rate limit with plug and a Redis-backed bucket

Add a rate-limiting plug before your Ecto repository calls. This example uses the hammer library with a Redis backend to enforce a limit of 30 requests per minute per user or IP.

# mix.exs
defp deps do
  [
    {:hammer, "~> 7.0"},
    {:redix, "~> 1.0"}
  ]
end

# config/config.exs
config :hammer,
  backend: {Hammer.Backend.RedisBackend, [Redix.start_link!(url: System.get_env("REDIS_URL") || "redis://localhost:6379")]},
  rate_limit: [
    %{name: "api:minute", limit: 30, period: 60}
  ]

# lib/my_app_web/plugs/rate_limit.ex
defmodule MyAppWeb.RateLimit do
  @behaviour Plug
  import Plug.Conn

  def init(opts), do: opts

  def call(conn, _opts) do
    key = "rate_limit:#{conn.ip |> :inet_parse.ntoa() |> to_string()}:#{conn.request_path}"
    case Hammer.check_rate(key, 60_000, 30) do
      {:allow, _} -> conn
      {:deny, _} ->
        conn
        |> put_resp_content_type("application/json")
        |> send_resp(429, Jason.encode!(%{error: "rate limit exceeded", retry_after: 60}))
        |> halt()
    end
  end
end

Plug this into your pipeline in lib/my_app_web/router.ex before any Ecto calls:

# lib/my_app_web/router.ex
pipeline :api do
  plug :accepts, ["json"]
  plug MyAppWeb.RateLimit
  plug MyAppWeb.Pipeline.db # your Ecto repo setup
end

2. Use Ecto transactions with retries and idempotency keys

When writing to CockroachDB via Ecto, make operations idempotent and keep transactions short to reduce contention. Use optimistic lock columns (e.g., lock_version) and a small retry wrapper for transient serialization errors.

# lib/my_app/accounts.ex
defmodule MyApp.Accounts do
  use Ecto.Schema
  import Ecto.Query
  alias MyApp.Repo

  schema "accounts" do
    field :balance, :integer
    field :lock_version, :integer, default: 0
    timestamps()
  end

  def transfer(from_id, to_id, amount) do
    retries = 3
    do_transfer(from_id, to_id, amount, retries)
  end

  defp do_transfer(from_id, to_id, amount, retries) when retries >= 0 do
    Repo.transaction(fn ->
      from = Repo.get!(Account, from_id, lock: "FOR UPDATE")
      to = Repo.get!(Account, to_id, lock: "FOR UPDATE")

      if from.balance < amount do
        raise Ecto.NoResultsError
      end

      Account.changeset(from, %{balance: from.balance - amount, lock_version: from.lock_version + 1})
      |> Repo.update!()

      Account.changeset(to, %{balance: to.balance + amount, lock_version: to.lock_version + 1})
      |> Repo.update!()
    end)
  rescue
    e in Ecto.StaleModelError ->
      if retries > 0 do
        :timer.sleep(50)
        do_transfer(from_id, to_id, amount, retries - 1)
      else
        reraise e
      end
  end
end

3. Protect endpoints at the router and use query cost analysis

For read-heavy endpoints, avoid unbounded queries and add pagination or time windows. In router pipelines, apply stricter limits for mutation routes that write to CockroachDB, and consider using ETS or a Redis counter for coarse-grained protections before issuing database queries.

# Example: limit payload size and pagination to reduce CockroachDB load
pipeline :read_api do
  plug :accepts, ["json"]
  plug MyAppWeb.RateLimit
  plug MyAppWeb.Pipeline.db
  plug MyAppWeb.Plugs.RequirePagination
end

By enforcing rate limits at the API edge and designing Ecto transactions to be short, idempotent, and retried safely, you prevent API-driven overloads that would otherwise stress CockroachDB’s serializable isolation and range coordination.