The Anonymity Gap: Understanding Real Privacy in Shielded UTXO-based Protocols for DeFi
2026-08-24 • Cryptography and Security
Cryptography and Security
AI summaryⓘ
The authors study privacy in shielded UTXO-based DeFi protocols, where assets can move privately inside a pool before becoming public upon withdrawal. They point out that anonymity depends on tracking the history of transactions (provenance) rather than just the size of the pool. To analyze this, they create a layered model that traces how privacy shrinks over time by examining all past interactions and constraints. Applying their method to real data from several deployments, they find that anonymity often decreases significantly and identify top reasons why privacy is lost. Their work helps understand how privacy leaks happen and may inform better protocol designs.
UTXODeFiShielded PoolAnonymity SetProvenanceCommitment SetTransaction HistoryZero-Knowledge ProofPrivacy ProtocolRailgun
Authors
Hanze Guo, Stefanos Chaliasos, Yebo Feng, Jiahua Xu
Abstract
Shielded UTXO-based protocols are becoming a core form of privacy infrastructure for DeFi. Unlike mixers that organize privacy mainly around deposits and withdrawals, these protocols allow assets, once inside the shielded pool, to continue moving and being re-spent within the hidden state, and to become public only when users withdraw or interact with public DeFi protocols. Their anonymity is therefore no longer a flat pool-size problem, but a provenance problem that propagates across the note/UTXO, proof, and transaction layers. Yet, a unified analysis framework for this setting is still missing. We propose a layered system model and an analysis pipeline that uses prior history as the temporal baseline, applies cumulative pruning and cross-proof propagation to each proof's Commitment Set, and recursively traces the survivors through historical hidden-state transitions to derive the final transaction-level Anonymity Set Size. We evaluate our methodology on the complete on-chain histories of all four Railgun production deployments and five independent Hinkal pools across six EVM chains, analyzing 186,356 unshielding spend transactions. Using only public protocol traces and constraints, our non-heuristic analysis yields mean Anonymity Set Size reductions of 40.1%-59.0% relative to each deployment's temporal baseline; 3,679 transactions retain at most 10 addresses, including 1,228 singletons. Public token constraints are the strongest and most stable source of pruning in both protocols, while the effects of tree number, proof roots, and value constraints vary with protocol design and historical state. Together with representative cases, these results reveal interpretable anonymity-loss patterns and implications for user behavior and future protocol design.