Api Rate Abuse in Buffalo with Basic Auth

Rate abuse in Buffalo applications that rely on HTTP Basic Authentication occurs when an attacker can make a high volume of requests to authentication-protected endpoints without sufficient enforcement of request limits. Basic Auth transmits credentials on each request as a base64-encoded string in the Authorization header; while this encoding is not encryption, the presence of credentials does not inherently prevent automated brute-force or credential-stuffing attempts. The vulnerability emerges when rate limiting is absent or misconfigured, allowing an attacker to iterate over many usernames and passwords rapidly, testing stolen or guessed credentials against a login or token endpoint.

In Buffalo, this typically maps to routes under resources/sessions_controller.ex that handle login forms and token issuance. If these endpoints lack per-identifier or global rate limits, an attacker can submit many authentication requests within a short window, probing for valid accounts. Because Basic Auth is stateless and each request includes credentials, the server may process each request independently, making it easier to saturate rate-based defenses that rely on IP address alone. Attackers can rotate source IPs or use botnets to bypass simple IP-based throttling, especially when the application does not tie rate limits to user identity or API keys once authentication is established.

Additionally, Buffalo applications that expose public endpoints for authentication—such as preflight or health checks—may inadvertently allow unauthenticated probing at a higher rate than authenticated paths. Without aligning rate limits across authenticated and unauthenticated surfaces, an attacker can use the unauthenticated path to enumerate behavior, then pivot to authenticated routes once valid credentials are obtained. The combination of Basic Auth and missing or inconsistent rate limiting also increases the risk of credential leakage via logs or error messages if attackers trigger numerous failed attempts, potentially aiding further post-exploitation activities.

Middleware or firewall-level protections may not fully mitigate this risk if limits are applied after the request reaches the application layer or if they do not consider the semantics of authentication failures. Because Buffalo does not enforce application-level rate limits by default, developers must explicitly configure throttling mechanisms and ensure they account for the presence of Basic Auth headers when deciding whether a request should be allowed or denied.

Remediation focuses on introducing rate limits that consider authentication context and ensure credentials are handled safely. Implement per-username or per-IP throttling for authentication endpoints, and avoid allowing unlimited attempts for any given identifier. Below are concrete code examples for applying rate limiting in a Buffalo application using plug-based approaches and Redis-backed counters.

Example 1: A plug that enforces rate limits based on a combination of IP and Basic Auth username when credentials are present. This helps prevent targeted brute-force against specific accounts while still allowing reasonable traffic for legitimate users.

defmodule MyApp.RateLimit do
  import Plug.Conn
  import Phoenix.Controller, only: [json: 2, put_status: 2]

  @max_requests 30
  @window_ms 60_000

  def init(opts), do: opts

  def call(conn, opts) do
    key = case get_req_header(conn, "authorization") do
      ["Basic " <> encoded] ->
        case Base.decode64(encoded) do
          {:ok, "#{username}:_}" -> {:username, username}
          _ -> {:ip, conn.remote_ip}
        end
      _ ->
        {:ip, conn.remote_ip}
    end

    cache_key = "rate_limit:#{key}"
    current = Redis.incr(cache_key)
    if current == 1, do: Redis.expire(cache_key, div(@window_ms, 1000))

    if current > @max_requests do
      conn
      |> put_status(429)
      |> json(%{error: "Too Many Requests"})
      |> halt()
    else
      conn
    end
  end
end

Example 2: Applying the rate limit plug only to authentication routes in the router, ensuring that non-auth endpoints are not subject to the same constraints unless required.

defmodule MyAppWeb.Router do
  use MyAppWeb, :router
  import MyApp.RateLimit

  pipeline :browser do
    plug :accepts, ["html"]
  end

  scope "/", MyAppWeb do
    pipe_through :browser

    get "/", PageController, :index
  end

  scope "/api", MyAppWeb do
    pipe_through :api

    post "/sessions", SessionController, :create, plugs: [RateLimit]
  end
end

Example 3: Using a token-bucket or sliding window algorithm via Redis for more nuanced control, particularly when usernames are available after an initial unauthenticated probe. This approach reduces the likelihood of false positives for legitimate users sharing the same IP (e.g., behind NAT).

defmodule MyApp.RateLimit.SlidingWindow do
  @max_requests 10
  @window_seconds 60

  def allow?(identifier) do
    key = "rl:#{identifier}"
    now = System.system_time(:second)
    window_start = now - @window_seconds

    # Remove outdated timestamps
    Redis.zremrangebyscore(key, 0, window_start)
    # Count current requests
    count = Redis.zcard(key)
    if count < @max_requests do
      Redis.zadd(key, now, "#{now}:#{:crypto.strong_rand_bytes(8)}")
      Redis.expire(key, @window_seconds)
      true
    else
      false
    end
  end
end

In all cases, ensure that error responses do not disclose whether a username exists, to prevent user enumeration via rate-limited endpoints. Combine these measures with transport-layer encryption and secure handling of Authorization headers to reduce the overall risk of credential exposure during repeated attempts.