🤖 AI Summary
This work addresses a critical yet overlooked class of vulnerabilities in cryptographic systems arising from the lack of a unique mapping between semantic objects and their byte representations, which can undermine mechanisms such as hashing, digital signatures, and replay protection due to representation inconsistencies. The paper presents the first systematic classification of these “representation divergence” vulnerabilities and introduces a unified framework that identifies two root causes: object-side multiple representations and encoding-side semantic collapse. By integrating formal modeling, field-type categorization, and operational boundary analysis, the authors develop an actionable canonicalization obligation review process. This approach transcends specific system implementations, establishing a general taxonomy grounded in representation mechanisms, bridging classical canonicalization security with computability theory, and demonstrating its efficacy and applicability through multiple real-world case studies.
📝 Abstract
Cryptographic systems operate on bytes but mean semantic objects. The translation between the two is rarely unique. Where this uniqueness is not enforced, an attack surface opens up as soon as a hash, a signature, replay protection, or consensus identity depends on the representation. The same class of failure has been discovered independently and named locally across many ecosystems, as transaction malleability, non-deterministic value encoding, message malleability, or hash chain malleability, without its common root being tracked as a cross-ecosystem grid. This work organizes the scattered findings systematically: it shows that they are instances of one violated uniqueness condition, along two basic directions: multiple valid codes for one object (object-side multiple representation) or one code for multiple objects (code-side semantic collapse). The contribution is explicitly not the discovery of the phenomenon, but is threefold: the systematization by representation mechanism rather than by affected system, the bridge between classical canonicalization security and a representation- and computability-theoretic foundation, and the translation into an applicable review procedure (a canonicalization obligation with a sequence of review steps, a field-type classification, and an operational boundary model) with which the risk can be recognized preventively. We substantiate the class with worked-out cases, delimit it against incidents that are not representation problems, and deliberately keep the claims to what is demonstrable: enforced uniqueness can reduce the exploitability of a failure class, but it neither replaces further protective measures or makes any statement about cryptographic security in the narrower sense