Api Rate Abuse in Hanami with Hmac Signatures

Hanami is a Ruby web framework that encourages explicit routing and controller design. When Hmac Signatures are used for request authentication—typically by having clients sign a canonical string with a shared secret and sending the signature in a header—rate-limiting controls must account for both the signature and the underlying request characteristics. If rate limiting is applied only after signature verification and relies on data that an attacker can influence (such as path, HTTP method, or selected headers), an attacker may generate many distinct, valid signed requests that each pass authentication but still exhaust server-side resources or quotas.

A common pattern is to compute the Hmac over a combination of HTTP method, path, selected headers, and a timestamp to prevent replay. However, if the rate limit key is derived from incomplete information—omitting the request body or query parameters that an attacker can vary—the same signed context may be reused in ways the server did not anticipate. For example, a POST to /transfers with different JSON bodies could be treated as distinct requests if the body is excluded from the rate-limit key but included in the business logic, allowing an attacker to flood specific operations while staying within a per-minute signature budget.

Another risk arises when timestamps are included in the signed string without strict server-side validation of clock skew and replay windows. An attacker can slightly adjust timestamps within an allowed window, creating new signatures that are technically valid and rate-limited under different time buckets, effectively bypassing aggregate limits. Additionally, if the server does not enforce a strict rate limit on the number of signature verification attempts per client identifier, an attacker can probe many candidate signatures or flood the endpoint with rejected requests, consuming CPU cycles and connection capacity even when successful writes are prevented.

These combinations illustrate why Api Rate Abuse is not solely about limiting request counts; it must consider how authentication metadata (Hmac Signatures) interacts with the scope of the rate limit key, the validation of temporal nonces, and the treatment of mutable request components. Without aligning the rate-limiting context with the authenticated context, an attacker can exploit subtle gaps to degrade availability or drive up compute costs.

Remediation centers on normalizing the rate-limit key to include all components that define the authenticated context and are controlled by the client, while enforcing strict validation rules. The server should derive the rate-limit key from a canonical representation that covers HTTP method, path, selected headers, query parameters, and, when applicable and safe, a hash of the request body for idempotent-safe operations. Timestamps used for replay protection must be validated within a tight server-side window and excluded from any data that influences business logic after verification.

Below are Hanami-inspired code examples that demonstrate how to compute a stable Hmac signature and a corresponding rate-limit key. These snippets assume you have a shared secret available as ENV["HMAC_SECRET"].

Building a canonical string and Hmac signature

require "openssl"
require "base64"
require "uri"

def canonical_string(request)
  # Include method, full path (without domain), selected headers, and query params
  # to ensure the rate-limit key matches the authenticated context.
  path = request.env["REQUEST_PATH"] || ""
  query = request.env["QUERY_STRING"]
  query_part = query.empty? ? "" : "?#{query}"
  method = request.request_method.upcase

  # Select headers that are part of the authentication scheme; keep order stable.
  headers_to_sign = %w[content-type x-request-id].map { |h| request.env["HTTP_#{h.upcase.gsub('-', '_')}"] }.compact.join("|")

  # For POST/PUT/PATCH, include a hash of the body to prevent body-based bypass.
  body_hash = if %w[POST PUT PATCH].include?(method) && request.body && request.body.size.positive?
                Digest::SHA256.base64digest(request.body.read)
              else
                ""
              end

  [method, path, query_part, headers_to_sign, body_hash].join("|")
end

def generate_hmac_signature(request)
  secret = ENV.fetch("HMAC_SECRET")
  message = canonical_string(request)
  hmac = OpenSSL::HMAC.digest("sha256", secret, message)
  Base64.strict_encode64(hmac)
end

Deriving a rate-limit key from the authenticated context

def rate_limit_key(request)
  # Include the client identifier (e.g., an API key or IP) and the canonical string.
  # This ensures each distinct authenticated context has its own rate bucket.
  client_id = request.env["HTTP_X_API_KEY"] || request.ip
  digest = Digest::SHA256.hexdigest(canonical_string(request))
  "rate_limit:#{client_id}:#{digest}"
end

With this approach, the rate limit key incorporates the method, path, selected headers, query parameters, and a safe body hash, making it difficult for an attacker to create many distinct valid keys without knowing the secret. Server-side validation should also enforce a narrow time window for timestamps used in replay protection and reject requests with significant clock skew.

Finally, ensure that rate limiting is applied before expensive business logic and that the number of verification attempts per client is bounded to prevent resource exhaustion via rejected requests. Combining these Hmac-aware rate-limiting practices with continuous monitoring (such as scanning with middleBrick) helps detect anomalies in authenticated traffic patterns.