Intent-based cross-chain bridges have emerged as an alternative to traditional interoperability protocols by allowing off-chain entities (solvers) to immediately fulfill users' orders by fronting their own liquidity. While improving user experience, this approach introduces new systemic risks, such as solver liquidity concentration and delayed settlement. In this paper, we propose a new class of attacks called liquidity exhaustion attacks and a replay-based parameterized attack simulation framework. We analyze 3.5 million cross-chain intents that moved $9.24B worth of tokens between June and November 2025 across three major protocols (Mayan Swift, Across, and deBridge), spanning nine blockchains. For rational attackers, our results show that protocols with higher solver profitability, such as deBridge, are vulnerable under current parameters: 210 historical attack instances yield a mean net profit of $286.14, with 80.5% of attacks profitable. In contrast, Across remains robust in all tested configurations due to low solver margins and very high liquidity, while Mayan Swift is generally secure but becomes vulnerable under stress-test conditions. Under byzantine attacks, we show that it is possible to suppress availability across all protocols, causing dozens of failed intents and solver profit losses of up to $978 roughly every 16 minutes. Finally, we propose an optimized attack strategy that exploits patterns in the data to reduce attack costs by up to 90.5% compared to the baseline, lowering the barrier to liquidity exhaustion attacks.

The proliferation of diverse blockchain networks has intensified the demand for interoperability, but cross-chain bridges introduce significant security risks. This paper proposes a protocol protection framework for early incident detection and containment through a runtime transactions conformance checking pipeline. Deviations from expected behavior trigger a pausing mechanism, halting operations to prevent incorrect state propagation across blockchains. Our evaluation shows that anomalies can be detected and cross-chain asset transfers paused in less than 10 seconds, reducing attack exposure and preventing cascading failures. The results highlight how automated pausing is a critical safeguard for securing interoperability infrastructures and strengthening cross-chain ecosystems.

In recent years, there has been a growing adoption of blockchain interoperability solutions and cross-chain protocols [1] , [5] . The most popular are cross-chain bridges or, simply, bridges. Bridges connect decentralized applications across various blockchains, supporting the transfer and exchange of assets between blockchains. Cross-chain bridges now have tens of billions of total value locked (TVL). However, this growth has also led to the theft of billions in cross-chain protocols [1] . Not even extensively audited bridges are immune to vulnerabilities [7] .

In the last decade, blockchain interoperability solutions, especially cross-chain bridges, have become increasingly popular. However, the field still has considerable room for growth in addressing vulnerabilities and preventing system exploitation. In this work, we propose a novel classification scheme for evaluating and benchmarking blockchain interoperability visualization mechanisms and identifying key gaps on cross-chain information availability. We also propose two mechanisms to streamline the cross-chain operation analysis process. The first is a dataset generation framework for cross-chain transactions that can fetch blockchain events from blockchains, aggregate them into cross-chain transactions, and record these transactions in an organized format for data analysis. The second is a visualization tool that shows users information on cross-chain operations based on an existing dataset. This position paper aims to bring to light and address gaps in blockchain interoperability with the intention of enabling and catalyzing the development of future solutions, ultimately contributing to a more mature blockchain interoperability ecosystem.

The number of blockchain interoperability protocols for transferring data and assets between blockchains has grown significantly. However, no open dataset of cross-chain transactions exists to study interoperability protocols in operation. There is also no tool to generate such datasets and make them available to the community. This paper proposes XChainDataGen, a tool to extract cross-chain data from blockchains and generate datasets of cross-chain transactions (cctxs). Using XChainDataGen, we extracted over 35 GB of data from five cross-chain protocols deployed on 11 blockchains in the last seven months of 2024, identifying 11,285,753 cctxs that moved over 28 billion USD in cross-chain token transfers. Using the data collected, we compare protocols and provide insights into their security, cost, and performance trade-offs. As examples, we highlight differences between protocols that require full finality on the source blockchain and those that only demand soft finality (\textit{security}). We compare user costs, fee models, and the impact of variables such as the Ethereum gas price on protocol fees (\textit{cost}). Finally, we produce the first analysis of the implications of EIP-7683 for cross-chain intents, which are increasingly popular and greatly improve the speed with which cctxs are processed (\textit{performance}), thereby enhancing the user experience. The availability of XChainDataGen and this dataset allows various analyses, including trends in cross-chain activity, security assessments of interoperability protocols, and financial research on decentralized finance (DeFi) protocols.

Blockchain technology has expanded into various domains, but the lack of interoperability standards remains a significant barrier to seamless communication and asset transfers between systems. The Secure Asset Transfer Protocol (SATP), developed by the Internet Engineering Task Force (IETF), offers a framework for cross-chain transfers but leaves key challenges like pre-transfer verification, asset specification, and trust assumptions unresolved. This work contributes to SATP by proposing an asset schema handling mechanism that addresses data formats and its integration with SATP's setup stage. A literature review of SATP-based and non-SATP solutions informs this proposal, which introduces a third-party certification authority to commission and validate asset schemas. The solution incorporates an Asset Definition Authority to mediate asset setup and is evaluated through a security-focused threat model. This research advances asset schema standardization and interoperability, providing a foundation for further exploration.

Cross-chain bridges are a blockchain interoperability middleware that supports the transfer of assets and data across blockchains. However, several of these bridges have vulnerabilities that have caused 3.2 billion dollars in losses since May 2021. Some studies have revealed the existence of these vulnerabilities, but there is little quantitative research available, and there are no safeguard mechanisms to protect bridges from such attacks. Furthermore, no studies are available on the practices of cross-chain bridges that can cause financial losses. We propose XChainWatcher (CrossChainWatcher), a modular and extensible logic-driven anomaly detector for cross-chain bridges. It operates in three main phases: (1) decoding events and transactions from multiple blockchains, (2) building logic relations from the extracted data, and (3) evaluating these relations against a set of detection rules. Using XChainWatcher, we analyze data from two previously attacked bridges: the Ronin and Nomad bridges. XChainWatcher successfully identified the transactions that led to losses of $611M and $190M (USD) and surpassed the results obtained by a reputable security firm in the latter. We not only uncover successful attacks, but also reveal other anomalies, such as 37 cross-chain transactions (cctx) that should not have accepted, failed attempts to exploit Nomad, over $7.8M worth of tokens locked on one chain but never released on Ethereum, and $200K lost by users due to inadequate interaction with bridges. We provide the first open dataset of 81,000 cctxs across three blockchains, capturing more than $4.2B in token transfers.

With the growing interest in blockchain technology, researchers and developers in different industries are shifting their attention to creating interoperability mechanisms. Existing mechanisms usually encompass asset exchanges, asset transfers, and general data transfers. However, most of the solutions based on these mechanisms only work for two permissionless blockchains falling short in use cases requiring more complex business relationships. Also, contrary to existing legacy systems, there is little standardization for cross-chain communication. Here we present MP-SATP, a resilient multi-party asset transfer protocol built on top of the Secure Asset Transfer Protocol (SATP). Furthermore, we enhance SATP's crash recovery mechanism that directly influences the reliability and performance of our solution. Using MP-SATP, we show how to perform N-to-N resilient asset transfers in permissioned environments by decoupling them into multiple 1-to-1 asset transfers. Our results demonstrate that the latency of the protocol is driven by the latency of the slowest 1-to-1 session; and how the usage of backup gateways avoid the overhead caused by rollbacks. Enterprise-grade environments such as supply-chain management systems can immediately leverage our solution to perform atomic multi-party asset transfers as shown by our use case.

Blockchain aggregators play an instrumental role in the evolution of blockchain technology, serving as pivotal enablers of interoperability, efficiency, and user accessibility in an increasingly decentralized digital world. However, the literature on this emerging technology is scarce and not systematized, making it harder for practitioners and researchers to understand the field. In this paper, we systematize blockchain aggregators, with a specific emphasis on bridge aggregators. We present an exhaustive analysis of a diverse array of token and message aggregators, each distinguished by its unique architecture. Our investigation delves into critical aspects of these aggregators, encompassing their functionality, security measures, pricing models, and latency characteristics. The objective of this research is to furnish readers-encompassing both users and developers-with insightful and actionable information, thereby facilitating informed navigation through the complex landscape of blockchain aggregators.

Blockchain aggregators play an instrumental role in the evolution of blockchain technology, serving as pivotal enablers of interoperability, efficiency, and user accessibility in an increasingly decentralized digital world. However, the literature on this emerging technology is scarce and is not systematized, making it harder for practitioners and researchers to understand the field. In this paper, we systematize bridge aggregators, a type of blockchain aggregators. We present an exhaustive analysis of a diverse array of token and message aggregators, each distinguished by its unique architecture. Our research delves into critical aspects of these aggregators, encompassing their functionality, security measures, pricing models, and latency. This research aims to provide readers, users, and developers with insightful and actionable information, facilitating informed navi-gation through the complex landscape of blockchain aggregators. We explore our findings and compare them with our intuitive expectations. We show that there is a value in centralizing token aggregators. Message aggregators are found to be more powerful but less efficient in transaction cost and latency. Finally, we propose a set of future research directions for practitioners.

Cross-chain bridges are a type of middleware for blockchain interoperability that supports the transfer of assets and data across blockchains. However, several of these bridges have vulnerabilities that have caused 3.2 billion dollars in losses since May 2021. Some studies have revealed the existence of these vulnerabilities, but there is little quantitative research available, and there are no safeguard mechanisms to protect bridges from such attacks. Furthermore, no studies are available on the practices of cross-chain bridges that can cause financial losses. We propose (Cross-Chain Watcher), a modular and extensible logic-driven anomaly detector for cross-chain bridges. It operates in three main phases: (1) decoding events and transactions from multiple blockchains, (2) building logic relations from the extracted data, and (3) evaluating these relations against a set of detection rules. Using , we analyze data from two previously attacked bridges: the Ronin and Nomad bridges. was able to successfully identify the transactions that led to losses of $611M and $190M (USD) and surpassed the results obtained by a reputable security firm in the latter. We not only uncover successful attacks, but also reveal other anomalies, such as 37 cross-chain transactions () that these bridges should not have accepted, failed attempts to exploit Nomad, over $7.8M worth of tokens locked on one chain but never released on Ethereum, and $200K lost by users due to inadequate interaction with bridges. We provide the first open dataset of 81,000 across three blockchains, capturing more than $4.2B in token transfers.

Recent years have witnessed significant advancements in cross-chain technology. However, the field faces two pressing challenges when it comes to security and privacy. Hacks on cross-chain bridges have led to monetary losses of around 3 billion USD, highlighting flaws in security models governing interoperability mechanisms (IMs) and the ineffectiveness of incident response frameworks. Additionally, the exploration of privacy within cross-chain scenarios remains relatively unexplored. Hackers benefit from extensive privacy, whereas users and bridge operators experience restricted privacy, thereby broadening the potential attack surface for adversaries. In this paper, we present the most comprehensive study to date on the security and privacy of blockchain interoperability. Our study employs a rigorous systematic literature review, yielding a corpus of 178 relevant documents, including 58 academic papers and 120 gray literature documents, out of a pool of 531. We systematically categorize 56 interoperability solutions based on a newly created taxonomy focusing on security and privacy considerations. Our dataset, comprising academic research, disclosures from bug bounty programs, and audit reports, exposes 45 cross-chain vulnerabilities, 25 theoretical attacks, and 88 mitigation strategies. Leveraging this data, we analyze 14 notable bridge hacks accounting for over USD 2.9 billion in losses, mapping them to the identified vulnerabilities. Our findings reveal that a substantial portion (65.8\%) of stolen funds originates from projects secured by permissioned intermediary networks with unsecured cryptographic key operations. Regarding privacy, we demonstrate that achieving unlinkability in cross-chain transactions is contingent on the underlying ledgers providing some form of confidentiality. In conclusion, our study offers critical insights into the challenges and vulnerabilities within the realm of cross-chain interoperability. We pinpoint promising directions for future research that can guide both industry practitioners and academics toward substantial advancements in this field. Our work underscores the urgency of enhancing security and privacy measures in cross-chain technology to mitigate the substantial financial risks associated with bridge hacks and to foster user trust in the blockchain ecosystem.

The last few years have seen a steep increase in blockchain interoperability research. Most solutions connect public blockchains; hence, the main cross-chain use case is token transfer. By-design platform transparency, tamper-resistance, and auditability make blockchains an infrastructure candidate for Central Bank Digital Currencies (CBDCs), but bridging CBDCs is an important missing piece in general. In this paper, we leverage an asset transfer protocol, ODAP/SATP, to define an extendable and dependable blockchain interoperability middleware that can bridge CBDC from Hyperledger Fabric to EVM-based permissioned blockchains. The key interoperation enabler in the solution is a shared asset definition enforced by both sides of the bridge, accompanied by a mapping between Fabric Identities and Ethereum addresses for Identity management. We implement our design for the CBDC use case utilizing Hyperledger Cactus. Through a preliminary performance evaluation, we show that the underlying ledgers heavily influence the latency of the solution, not the bridging components.

<p>New applications and solutions are emerging as blockchain technology continues to prosper in different industries. However, blockchain systems are considered isolated silos, especially when it comes to interoperability on systems putting restrictions on handling private data. </p> <p>We propose ODAP-AS, a resilient N-N cross-chain asset transfer protocol that enables the execution of N transfers of assets in permissioned environments, leveraging the concept of gateways. Gateways act as the devices through which a blockchain network can be accessed. We build our protocol on top of the Open Digital Asset Protocol (ODAP), and its crash recovery mechanism, ODAP-2PC, a crash fault-tolerant protocol.</p> <p>ODAP-AS also defines how one gateway is replaced by a backup in case of a crash. We implement a cross-chain asset transfer across Hyperledger Fabric and Hyperledger Besu using Hyperledger Cactus, which takes approximately 20 seconds. Additionally, we can conduct a sequential execution of ODAP-AS achieving 0.15 transactions/second throughput.</p>