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Xihan Xiong

Publications and source records attributed to Xihan Xiong.

12 recordsLinked to original sources

Can Trustless Agents Be Trusted? An Empirical Study of the ERC-8004 Decentralized AI Agent Ecosystem

As autonomous AI agents increasingly transact across organizational boundaries, a fundamental trust challenge emerges: how can an agent assess whether an unknown counterpart is trustworthy? The ERC-8004 protocol addresses this challenge with the first permissionless trust layer for AI agent economies, built around three on-chain registries for Identity, Reputation, and Validation. Despite its rapid adoption, the protocol has not been studied empirically, leaving it unclear whether the information it records provides a trustworthy basis for decision-making. To address this gap, we present the first empirical study of ERC-8004 across three chains: Ethereum, BNB Smart Chain (BSC), and Base, covering the period from protocol deployment through May 13, 2026. We crawl on-chain Identity and Reputation events, off-chain files, and x402 payment transactions. On the identity side, we find that most registrations are placeholders rather than active agents, with only a small fraction (3%, 4%, and 15% across Ethereum, BSC, and Base) exposing a valid ERC-8004 registration file with at least one live service endpoint. On the reputation side, we show that the Registry, as currently deployed, cannot function as a trust signal: values are not commensurable, feedback records are rarely grounded in verifiable interactions, and reputation can be manipulated at minimal cost. Consistent with these design weaknesses, we find that a substantial fraction of reviewers (73.5%, 59.2%, and 90.6% across Ethereum, BSC, and Base) exhibit coordinated Sybil behavior. After removing Sybil-flagged feedback, 15.8%, 77.9%, and 86.8% of rated agents, respectively, are left with no valid feedback. We then turn these findings into concrete recommendations for future revisions of ERC-8004. Our study yields actionable protocol-design implications and establishes an empirical baseline for research on AI agent markets.

cs.CR

SoK of RWA Tokenization: A Systematization of Concepts, Architectures, and Legal Interoperability

The global financial architecture is undergoing a shift from intermediary centric-settlement to programmable infrastructure, to transmute trillions in static illiquid capital into active, high-velocity instruments. We argue that Real World Asset (RWA) tokenization represents a conceptual evolution beyond mere digitization, converting passive ledger entries into programmable economic agents capable of autonomous settlement and algorithmic collateralization. However, achieving such seamless capital efficiency necessitates resolving the fundamental friction between deterministic on-chain code and probabilistic off-chain reality, navigating the oracle problem and jurisdictional interoperability. This systematization of knowledge presents a taxonomy for the RWA lifecycle and deconstructs the multi-layered architecture, spanning legal custody, technical standards, and cryptoeconomic valuation, required to enforce off-chain rights within on-chain environments. We study systemic constraints such as latency and regulatory fragmentation through a comparative overview of sovereign debt, private credit, and real estate protocols, complemented by an empirical case study of on-chain U.S. Treasuries. We synthesize these findings to propose a prognostic outlook, positing that while asset tokenization provides a transitional bridge, it is not necessarily the inevitable shift compared to the emergence of unified, programmable ledgers.

q-fin.GN

In the Margins: An Empirical Study of Ethereum Inscriptions

Ethereum Inscriptions (Ethscriptions) repurpose Ethereum calldata into a persistent inscription channel by embedding \texttt{data:}~URI payloads. These transactions typically target externally owned accounts, allowing the payload to bypass EVM execution while remaining permanently replicated across full nodes. Although calldata was originally designed for compact smart-contract parameters, this repurposing enables structured data embedding with long-term storage consequences. We present the first large-scale empirical study of Ethscriptions, treating them as a distinct \emph{calldata-resident workload} rather than merely a subset of general calldata usage. Our analysis focuses on the \textit{Ethscription} operational subset, which consists of payloads that decode to JSON and conform to a token-operation grammar (e.g., \texttt{p}, \texttt{op}, \texttt{tick}, \texttt{amt}). From $6.27$ million Ethscription candidates (\Uone), we extract $4.75$ million Ethscription operations (\Utwo, $75.8\%$ of \Uone). This result shows that structured token-like activity dominates the ecosystem. Our measurements further reveal (i) a complete workload lifecycle compressed into nine months (bootstrap, expansion, saturation), (ii) proliferation of $30$+ competing protocols without convergence toward a dominant standard, (iii) a lifecycle funnel exhibiting $201\times$ deploy-to-mint amplification and a $57.6{:}1$ mint-to-transfer collapse indicative of speculative minting, (iv) extreme participation inequality (Gini~$0.86$), and (v) a measurable permanent data footprint imposed on the Ethereum network.

cs.CE

SoK: Blockchain-Based Decentralized AI (DeAI)

Centralization enhances the efficiency of Artificial Intelligence (AI) but also introduces critical challenges, including single points of failure, inherent biases, data privacy risks, and scalability limitations. To address these issues, blockchain-based Decentralized Artificial Intelligence (DeAI) has emerged as a promising paradigm that leverages decentralization and transparency to improve the trustworthiness of AI systems. Despite rapid adoption in industry, the academic community lacks a systematic analysis of DeAI's technical foundations, opportunities, and challenges. This work presents the first Systematization of Knowledge (SoK) on DeAI, offering a formal definition, a taxonomy of existing solutions based on the AI lifecycle, and an in-depth investigation of the roles of blockchain in enabling secure and incentive-compatible collaboration. We further review security risks across the DeAI lifecycle and empirically evaluate representative mitigation techniques. Finally, we highlight open research challenges and future directions for advancing blockchain-based DeAI.

cs.LG

Toxic Ink on Immutable Paper: Content Moderation for Ethereum Input Data Messages (IDMs)

Decentralized communication is becoming an important use case within Web3. On Ethereum, users can repurpose the transaction input data field to embed natural-language messages, commonly known as Input Data Messages (IDMs). However, as IDMs gain wider adoption, there has been a growing volume of toxic content on-chain. This trend is concerning, as Ethereum provides no protocol-level support for content moderation. We propose two moderation frameworks for Ethereum IDMs: (i) BUILDERMOD, where builders perform semantic checks during block construction; and (ii) USERMOD, where users proactively obtain moderation proofs from external classifiers and embed them in transactions. Our evaluation reveals that BUILDERMOD incurs high block-time overhead, which limits its practicality. In contrast, USERMOD enables lower-latency validation and scales more effectively, making it a more practical approach in moderation-aware Ethereum environments. Our study lays the groundwork for protocol-level content governance in decentralized systems, and we hope it contributes to the development of a decentralized communication environment that is safe, trustworthy, and socially responsible.

cs.CR

Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs)

Can you imagine, blockchain transactions can talk! In this paper, we study how they talk and what they talk about. We focus on the input data field of Ethereum transactions, which is designed to allow external callers to interact with smart contracts. In practice, this field also enables users to embed natural language messages into transactions. Users can leverage these Input Data Messages (IDMs) for peer-to-peer communication. This means that, beyond Ethereum's well-known role as a financial infrastructure, it also serves as a decentralized communication medium. We present the first large-scale analysis of Ethereum IDMs from the genesis block to February 2024 (3134 days). We filter IDMs to extract 867,140 transactions with informative IDMs and use LLMs for language detection. We find that English (95.4%) and Chinese (4.4%) dominate the use of natural languages in IDMs. Interestingly, English IDMs center on security and scam warnings (24%) with predominantly negative emotions, while Chinese IDMs emphasize emotional expression and social connection (44%) with a more positive tone. We also observe that longer English IDMs often transfer high ETH values for protocol-level purposes, while longer Chinese IDMs tend to involve symbolic transfer amounts for emotional intent. Moreover, we find that the IDM participants tend to form small, loosely connected communities (59.99%). Our findings highlight culturally and functionally divergent use cases of the IDM channel across user communities. We further examine the security relevance of IDMs in on-chain attacks. Many victims use them to appeal to attackers for fund recovery. IDMs containing negotiations or reward offers are linked to higher reply rates. We also analyze IDMs' regulatory implications. Their misuse for abuse, threats, and sexual solicitation reveals the urgent need for content moderation and regulation in decentralized systems.

cs.CR

Leverage Staking with Liquid Staking Derivatives (LSDs): Opportunities and Risks

In the Proof of Stake (PoS) Ethereum ecosystem, users can stake ETH on Lido to receive stETH, a Liquid Staking Derivative (LSD) that represents staked ETH and accrues staking rewards. LSDs improve the liquidity of staked assets by facilitating their use in secondary markets, such as for collateralized borrowing on Aave or asset exchanges on Curve. The composability of Lido, Aave, and Curve enables an emerging strategy known as leverage staking, an iterative process that enhances financial returns while introducing potential risks. This paper establishes a formal framework for leverage staking with stETH and identifies 442 such positions on Ethereum over 963 days. These positions represent a total volume of 537,123 ETH (877m USD). Our data reveal that 81.7% of leverage staking positions achieved an Annual Percentage Rate (APR) higher than conventional staking on Lido. Despite the high returns, we also recognize the potential risks. For example, the Terra crash incident demonstrated that token devaluation can impact the market. Therefore, we conduct stress tests under extreme conditions of significant stETH devaluation to evaluate the associated risks. Our simulations reveal that leverage staking amplifies the risk of cascading liquidations by triggering intensified selling pressure through liquidation and deleveraging processes. Furthermore, this dynamic not only accelerates the decline of stETH prices but also propagates a contagion effect, endangering the stability of both leveraged and ordinary positions.

q-fin.GN

Market Misconduct in Decentralized Finance (DeFi): Analysis, Regulatory Challenges and Policy Implications

Technological advancement drives financial innovation, reshaping the traditional finance landscape and redefining user-market interactions. The rise of blockchain and Decentralized Finance (DeFi) underscores this intertwined evolution of technology and finance. While DeFi has introduced exciting opportunities, it has also exposed the ecosystem to new forms of market misconduct. This paper aims to bridge the academic and regulatory gaps by addressing key research questions about market misconduct in DeFi. We begin by discussing how blockchain technology can potentially enable the emergence of novel forms of market misconduct. We then offer a comprehensive definition and taxonomy for understanding DeFi market misconduct. Through comparative analysis and empirical measurements, we examine the novel forms of misconduct in DeFi, shedding light on their characteristics and social impact. Subsequently, we investigate the challenges of building a tailored regulatory framework for DeFi. We identify key areas where existing regulatory frameworks may need enhancement. Finally, we discuss potential approaches that bring DeFi into the regulatory perimeter.

q-fin.CP

Exploring the Market Dynamics of Liquid Staking Derivatives (LSDs)

Staking has emerged as a crucial concept following Ethereum's transition to Proof-of-Stake consensus. The introduction of Liquid Staking Derivatives (LSDs) has effectively addressed the illiquidity issue associated with solo staking, gaining significant market attention. This paper analyzes the LSD market dynamics from the perspectives of both liquidity takers (LTs) and liquidity providers (LPs). We first quantify the price discrepancy between the LSD primary and secondary markets. Then we investigate and empirically measure how LTs can leverage such discrepancy to exploit arbitrage opportunities, unveiling the potential barriers to LSD arbitrages. In addition, we evaluate the financial profit and losses experienced by LPs who supply LSDs for liquidity provision. Our results show that 66% of LSD liquidity positions generate returns lower than those from simply holding the corresponding LSDs.

cs.CR

Decoding SEC Actions: Enforcement Trends through Analyzing Blockchain litigation using LLM-based Thematic Factor Mapping

The proliferation of blockchain entities (persons or enterprises) exposes them to potential regulatory actions (e.g., being litigated) by regulatory authorities. Regulatory frameworks for crypto assets are actively being developed and refined, increasing the likelihood of such actions. The lack of systematic analysis of the factors driving litigation against blockchain entities leaves companies in need of clarity to navigate compliance risks. This absence of insight also deprives investors of the information for informed decision-making. This study focuses on U.S. litigation against blockchain entities, particularly by the U.S. Securities and Exchange Commission (SEC) given its influence on global crypto regulation. Utilizing frontier pretrained language models and large language models, we systematically map all SEC complaints against blockchain companies from 2012 to 2024 to thematic factors conceptualized by our study to delineate the factors driving SEC actions. We quantify the thematic factors and assess their influence on specific legal Acts cited within the complaints on an annual basis, allowing us to discern the regulatory emphasis, patterns and conduct trend analysis.

cs.CL

Global Trends in Cryptocurrency Regulation: An Overview

Cryptocurrencies have evolved into an important asset class, providing a variety of benefits. However, they also present significant risks, such as market volatility and the potential for misuse in illegal activities. These risks underline the urgent need for a comprehensive regulatory framework to ensure consumer protection, market integrity, and financial stability. Yet, the global landscape of cryptocurrency regulation remains complex, marked by substantial variations in regulatory frameworks among different countries. This paper aims to study these differences by investigating the regulatory landscapes across various jurisdictions. We first discuss regulatory challenges and considerations, and then conduct a comparative analysis of international regulatory stances, approaches, and measures. We hope our study offers practical insights to enhance the understanding of global trends in cryptocurrency regulation.

cs.CY

SoK: Decentralized Finance (DeFi) Attacks

Within just four years, the blockchain-based Decentralized Finance (DeFi) ecosystem has accumulated a peak total value locked (TVL) of more than 253 billion USD. This surge in DeFi's popularity has, unfortunately, been accompanied by many impactful incidents. According to our data, users, liquidity providers, speculators, and protocol operators suffered a total loss of at least 3.24 billion USD from Apr 30, 2018 to Apr 30, 2022. Given the blockchain's transparency and increasing incident frequency, two questions arise: How can we systematically measure, evaluate, and compare DeFi incidents? How can we learn from past attacks to strengthen DeFi security? In this paper, we introduce a common reference frame to systematically evaluate and compare DeFi incidents, including both attacks and accidents. We investigate 77 academic papers, 30 audit reports, and 181 real-world incidents. Our data reveals several gaps between academia and the practitioners' community. For example, few academic papers address "price oracle attacks" and "permissonless interactions", while our data suggests that they are the two most frequent incident types (15% and 10.5% correspondingly). We also investigate potential defenses, and find that: (i) 103 (56%) of the attacks are not executed atomically, granting a rescue time frame for defenders; (ii) SoTA bytecode similarity analysis can at least detect 31 vulnerable/23 adversarial contracts; and (iii) 33 (15.3%) of the adversaries leak potentially identifiable information by interacting with centralized exchanges.

cs.CR