Paper 2019/987

Subverting Decryption in AEAD

Marcel Armour and Bertram Poettering


This work introduces a new class of Algorithm Substitution Attack (ASA) on Symmetric Encryption Schemes. ASAs were introduced by Bellare, Paterson and Rogaway in light of revelations concerning mass surveillance. An ASA replaces an encryption scheme with a subverted version that aims to reveal information to an adversary engaged in mass surveillance, while remaining undetected by users. Previous work posited that a particular class of AEAD scheme (satisfying certain correctness and uniqueness properties) is resilient against subversion. Many if not all real-world constructions - such as GCM, CCM and OCB - are members of this class. Our results stand in opposition to those prior results. We present a potent ASA that generically applies to any AEAD scheme, is undetectable in all previous frameworks and which achieves successful exfiltration of user keys. We give even more efficient non-generic attacks against a selection of AEAD implementations that are most used in practice.In contrast to prior work, our new class of attack targets the decryption algorithm rather than encryption. We argue that this attack represents an attractive opportunity for a mass surveillance adversary. Our work serves to refine the ASA model and contributes to a series of papers that raises awareness and understanding about what is possible with ASAs.

Available format(s)
Secret-key cryptography
Publication info
Published elsewhere. IMACC 2019
Algorithm Substitution AttacksPrivacySymmetric EncryptionMass Surveillance
Contact author(s)
marcel armour 2017 @ rhul ac uk
2020-01-09: revised
2019-09-02: received
See all versions
Short URL
Creative Commons Attribution


      author = {Marcel Armour and Bertram Poettering},
      title = {Subverting Decryption in AEAD},
      howpublished = {Cryptology ePrint Archive, Paper 2019/987},
      year = {2019},
      doi = {10.1007/978-3-030-35199-1_2},
      note = {\url{}},
      url = {}
Note: In order to protect the privacy of readers, does not use cookies or embedded third party content.