Beast Attack in Hanami with Hmac Signatures

A Beast Attack (Breaking the Encryption Scheme with Adaptive Chosen-Plaintexts) exploits patterns in how an application uses block ciphers with predictable initialization vectors (IVs). When HMAC signatures are applied after encryption without careful design, the combination can amplify risks by exposing whether an attacker can learn something about the plaintext through signature validity and side-channel behavior.

In Hanami, if you encrypt a session or message with a block cipher (e.g., AES-CBC) using a static or predictable IV and then compute an HMAC over the ciphertext with a separate key, the workflow often looks like this: generate an IV, encrypt payload, compute HMAC(IV + ciphertext), and send or store both the IV, ciphertext, and signature. If an attacker can submit chosen plaintexts and observe whether the resulting HMAC validates (for example, through error messages or timing differences), they may infer information about other ciphertexts. This happens because the IV is not properly randomized per encryption and the HMAC does not protect the integrity of the IV in a way that prevents adaptive attacks.

Hanami applications that use HMAC signatures for authenticity but rely on default or reused IVs can inadvertently create a scenario where the Beast Attack surface emerges. For example, suppose an endpoint accepts a cookie containing an encrypted blob and an HMAC; if the IV is static or only changes slowly, an attacker can craft many plaintexts, observe signature validity, and gradually recover plaintext blocks. The vulnerability is not in HMAC itself—Hmac-SHA256 remains a strong primitive—but in how it is composed with encryption when IV handling and verification logic are underspecified.

An additional exposure arises when applications do not verify the HMAC before decryption (or verify it in a way that leaks timing). If the server decrypts first and then computes HMAC, or uses a non-constant-time comparison, subtle timing differences can allow an attacker to learn about signature correctness and, consequently, about the relationship between chosen plaintexts and the encrypted data. This is especially important when the same key is used for both encryption and signing, or when key separation is not enforced, increasing the chance that a Beast Attack against the cipher mode translates into a practical exploit in the Hanami app.

To map this to real-world risks, consider an API that returns encrypted, HMAC-signed tokens without ensuring unique IVs per request and without strict input validation. Using middleBrick’s scan, such an endpoint might surface findings related to BFLA (Business Logic Flaws and Abuse) and Input Validation, because the token handling logic does not adequately isolate encryption contexts. The scan does not exploit the flaw but highlights that the composition of encryption and HMAC signatures can lead to insecure patterns that an attacker might leverage in a targeted Beast Attack.

Remediation centers on ensuring unique, unpredictable IVs for each encryption, verifying HMAC before any decryption, using constant-time comparison, and separating keys for encryption and signing. Below are concrete Hanami examples that follow these principles.

Secure encryption with HMAC and unique IV

Use a cryptographically secure random IV for each encryption, include it with the ciphertext, and compute the HMAC over the concatenated IV and ciphertext. Verify the HMAC before attempting decryption.

require 'openssl'
require 'base64'

module SecureToken
  ENC_KEY = OpenSSL::Cipher.new('aes-256-cbc').random_key
  SIGN_KEY = OpenSSL::HMAC.digest('sha256', 'signing-specific-salt', ENC_KEY)

  def self.generate(payload)
    iv = OpenSSL::Random.random_bytes(16)
    cipher = OpenSSL::Cipher.new('aes-256-cbc')
    cipher.encrypt
    cipher.key = ENC_KEY
    cipher.iv = iv
    ciphertext = cipher.update(payload) + cipher.final
    signature = OpenSSL::HMAC.hexdigest('sha256', SIGN_KEY, iv + ciphertext)
    Base64.strict_encode64(iv + ciphertext + signature)
  end

  def self.verify_and_decrypt(token)
    raw = Base64.strict_decode64(token)
    iv = raw[0..15]
    ciphertext = raw[16..-33]
    signature = raw[-32..]
    expected = OpenSSL::HMAC.hexdigest('sha256', SIGN_KEY, iv + ciphertext)
    unless secure_compare(expected, signature)
      raise ArgumentError, 'Invalid signature'
    end
    decipher = OpenSSL::Cipher.new('aes-256-cbc')
    decipher.decrypt
    decipher.key = ENC_KEY
    decipher.iv = iv
    decipher.update(ciphertext) + decipher.final
  end

  def self.secure_compare(a, b)
    return false unless a.bytesize == b.bytesize
    l = a.unpack 'C*'
    res = 0
    b.each_byte.with_index { |byte, idx| res |= byte ^ l[idx] }
    res == 0
  end
end

# Usage:
token = SecureToken.generate('sensitive-session-data')
begin
  SecureToken.verify_and_decrypt(token)
rescue ArgumentError => e
  # Handle invalid signature safely
end

Hanami controller integration with constant-time verification

In a Hanami controller, validate the HMAC before any processing and avoid branching on secret-dependent data. Use the secure_compare helper to prevent timing leaks.

class Api::V1::SessionController < Hanami::Controller
  def create
    token = params[:token]
    begin
      payload = SecureToken.verify_and_decrypt(token)
      # proceed with authenticated session setup
      render json: { status: 'ok' }
    rescue ArgumentError
      # Always return a generic error to avoid information leakage
      halt 401, { error: 'invalid_token' }.to_json
    end
  end
end

Key and IV best practices

• Generate a new IV for every encryption operation using a CSPRNG (OpenSSL::Random.random_bytes).
• Derive signing and encryption keys from a master secret using a KDF (e.g., HKDF) or at least separate key material to avoid key reuse.
• Always verify HMAC before decryption and use constant-time comparison to prevent timing attacks.
• Do not reuse nonces/IVs with the same key for the same cipher mode.

By applying these patterns, Hanami applications avoid weak IV handling and ensure that HMAC signatures are verified safely, mitigating risks that could be exploited in a Beast Attack or via signature oracle behaviors. The code examples above align with secure composition practices and can be integrated into services monitored by middleBrick’s scans to confirm improved security posture.