And for Optimistically verified bridges, they have a delay built in the bridge model itself which means that these types of risks can be easily detected and reacted to, without having to change any fundamental bridge design. For externally verified systems, it is easy to add delay and off-chain verification but not necessarily required for the bridge. One example of a weak environment security would be, connecting a less secure blockchain to a more secure one such as Cardano to Ethereum. So if we compare the three bridge security models, in terms of implementation security, starting with the most secure, #1 is Optimistically verified, #2 is Externally verified and #3 is Natively verified.
1 Reasons why bridges get hacked
- This is how Ronin Bridge was hacked – their smart contracts were sound, with good audits and quality code, but the traditional security foundation was lacking.
- Some bridges connect just two blockchains, other bridges connect a lot of blockchains at the same time, which exposes them to a large number of attack vectors.
- Developers can embed CCTP into their apps and provide users with the most capital efficient way to transfer USDC across chains.
- At the core of every bridge is a messaging infrastructure that sends data across chains.
- To conclude, bridges can be categorized in many ways, we’ve seen the categorization by validation method and the categorization by the applications built on top of the messaging infrastructure.
- It therefore makes sense that ZKPs are also being explored to formulate bridge constructions.
- ZkBridge is a framework that allows for the creation of applications that can communicate between different blockchain networks.
There could be a governance bridge that allows you to vote from different chains. In a nutshell, whenever one blockchain (eg. Ethereum) connects to any other blockchain (eg. Solana), there is a bridge (eg. Portal) involved leveraging a messaging infrastructure (e.g Wormhole). With the introduction of composability on Ethereum and building of smart contract protocols for various DeFi applications, the number of use cases grew, and Ethereum's initial design was no longer scalable. By taking this proactive approach, developers can protect the assets that their bridges handle and reduce the likelihood of their network being damaged. Thus, bridge hack is a growing problem, as bridges are a common target for attackers and we will discuss how developers can mitigate these attacks, respond to a hack, and assess the safety of a bridge through risk scoring.
Depending on the application, they can be a Token, NFT, Governance, Lending or an ENS bridge. Additionally, the use of aggregators adds an extra layer of risk to the implementation process. The use of bridge aggregators that allow for multi-step or multi-hop bridging increases the likelihood of a transaction failure. Additionally, computing the optimal routes off-chain reduces costs and enhances efficiency and user experience.
First, we gather all the relevant information about the protocol by answering a set of questions. In the Data Gathering section we answer several questions to gather the relevant data points needed for the Risk Scoring section. It expands on well-known conventional security concepts and uses domain-specific application weakness classification to provide a good analysis value. Joel John, a writer for Decentralised.co, who collaborated on this framework with the Socket team and has written a detailed piece titled ‘Assessing Blockchain Bridges’, expanding on each of these 5 categories. Vaibhav Chellani (Socket, Bungee Exchange), who wrote this framework has a Video Seminar centered around building the risk framework for Bridge Security where he discusses these 5 categories in details. Meaning that retail users might prefer a fully permissionless model, whereas institutions might want to use a permisionned and OFAC compliant one.
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Even for the 32 signature case, with 32 machines in the relay network, this leads to a relatively large number of rounds of communication in the network, which might completely kill the performance coming from distributed computation. One thing that seems to have escaped mention is that the relay network computation will suffer the same communication complexities as the MPC, and that will also affect the prover time. The deVirgo proof system is post quantum resistant since it only relies on collision resistant hash functions, and the main computational bottlenecks are Number Theoretic Transforms (NTT’s) in large sized circuits. In the first step, a deVirgo proof is generated, which is then compressed using the Groth16 prover. For a circuit that validates 100 signatures with about 10M gates, the proof size is 210KB (same as that of the Virgo prover).
zkbridge (Berkeley RDI)
Notwithstanding the fact that this goes against the very founding principles of blockchains, it brings with it issues related to censorship and security. Interchain communication in the multichain universe, often referred to as the interoperability layer, is a foundational infrastructure that acts as a bridge between different blockchains. A typical user interacts with a bridge by sending funds on a chain C1 to the bridge protocol that “locks” these funds into contract, i.e these funds are unusable in C1.
Lattice-based ZK Explained
However, the usage of a zk-SNARK lowers the trust assumptions which is in the end perhaps what we are looking for. Furthermore with the optimizations, it achieves low storage overhead, reduction in circuit complexity and succinct verification and appears generalizable. Optimizations include usage of the 512 Public key (PK) inputs of the validators as a commitment using a ZK friendly Poseidon hash.
One problem with liquidity networks is that the liquidity can dry up and the user will have to wait longer. Liquidity networks thus act as a crosschain DEX such that they allow you to swap tokens for a small fee. Liquidity networks are systems that allow you to swap these tokens from one chain to another. For decentralized bridges, a decentralized approach is used to affirm the message indicating that the asset has been burnt on one side and minted on the other. For centralized bridges, a single entity is responsible for verifying the burn process. This type of bridge has the advantage of allowing virtually limitless minting and burning (provided 6/8 nodes submit the same transactions to the SGX Enclave to sign), thus improving user experience by ensuring an absence of liquidity issues.
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Chainalysis data has revealed that bridge hacks have accounted for a staggering 69% of the total funds stolen in the DeFi space in the past two years. Different bridges use different mechanisms to ensure the message is valid and hence it is incredibly difficult to build fully secure bridges. Hacken is a blockchain security auditor born in 2017 with a vision of transforming Web3 into a safer place. To evaluate the security of different types of bridges, the three main pillars of bridge security, namely Economic Security, Implementation Security, and Environment Security need to be considered.
- For decentralized bridges, a decentralized approach is used to affirm the message indicating that the asset has been burnt on one side and minted on the other.
- These messages contain instructions for the smart contracts on the destination chain to create or release new tokens, which then completes the transaction.
- Vaibhav Chellani (Socket, Bungee Exchange), who wrote this framework has a Video Seminar centered around building the risk framework for Bridge Security where he discusses these 5 categories in details.
- As a bridge supports more and more networks, it increases the probability of being exploited.
- The backend is implemented entirely in Rust, designed to handle data aggregation, cryptographic computations, and cross-chain communication efficiently and securely.
- It is important to note that while only the origin chain can prove fraud, the destination chains can be disconnected by a trustworthy watcher.
One issue with this approach is latency, as the proof generation process needs to keep up with the high block production rate of the Cosmos SDK. And the target chain will then have some information about the source chain baked into its own consensus. The three main areas of security issues were bugs in the code, blindspots in the architecture (such as missing fail safes) and committee/validator takeovers. Synthetix uses TradingView to display data on charts, providing advanced tools to enhance your market research. Earn steady rewards without collateral ratio worries or liquidation risk. Built on Ethereum Mainnet, with the strongest asset security guarantee in DeFi.
The technology offers unparalleled security, transparency and trust, allowing users to securely store and transfer digital data, such as cryptocurrency, in a distributed and immutable manner. And lastly, having a standardized risk assessment framework can be useful from the users’ perspective to select the appropriate bridge for their transaction size and security needs. At the core of every bridge is a messaging infrastructure that sends data across chains.
Ronin bridge can also be categorized as somewhat centralized, although it was 5/9 multisig, but four of the multisig parties were stored by one operator essentially making it 2/9 for hackers. For example, if you swap from USDC on Ethereum, to USDC on Polygon using Coinbase, you're technically bridging USDC, though the method is externally verified we are unsure of the method as it is something centralized and non-transparent. With an external validator set, the trust lies on the bridge itself acting as an intermediary. Examples include Wormhole, Multichain, Axelar, DeBridge, Synapse, Stargate. This is a type of bridge where a 3rd party verifies the transactions. The implementation of a seven-day challenge period prior to exit provides an added layer of security as it allows ample time for the security team to identify and address any potential bugs.
Electron Labs is trying to create a connection between the Cosmos SDK ecosystem, which is a framework for building specific blockchain applications, and Ethereum. If at least 2/3 of the validators sign a given block header, the state of the Ethereum network is considered valid. The Ethereum 2.0 network has a committee of 512 validators randomly chosen every 27 hours and is responsible for signing every block header during that period. The system uses SNARKS to efficiently verify the validity of consensus proofs on the Gnosis chain.
Succinct Labs has built a light client for Ethereum 2.0 proof of stake consensus to construct a trust minimized bridge between Gnosis and Ethereum, that uses the succinct properties of zk-SNARKS (not Zero Knowledge) to efficiently verify consensus validity proofs on-chain. However, there are certain steps developers can take to prevent these attacks and respond promptly in case of a hack, while users of the bridge can assess the safety of a bridge by evaluating its risk score. These can be vulnerable in many ways such as stealing signer keys, collaborating with validators, maliciously updating smart contracts, exploiting smart contract bugs, compromising RPC endpoints, or undergoing re-org attacks, among others. Bridges are the solutions to ease fragmentation and allow users to hop from one blockchain to another seamlessly.
This is achieved by proving the correctness of information without exposing the data itself, a crucial feature for maintaining privacy and security. Ethereum, Polygon and Avalanche are integrated as EVM-compatible chains, leveraging existing token standards and bridging solutions. This project leverages the power of Rust, zero-knowledge proofs (ZKPs), and cross-chain interoperability standards (like IBC and XCMP) to create a scalable and trust-minimized multichain platform. The main reason for security vulnerabilities are due to the way a bridge acts as a centralized storage unit. The current state of the blockchain ecosystem resembles a heterogeneous distribution of bubble universes (fragmented multichain universe), each with its own rules of consensus mechanism, design, applications, and use cases.
Avalanche bridge provides an example of a message based token bridge, in which tokens are locked/burned on one chain and minted/unlocked on the other. Based on spinmaya casino bonus the VAA user can withdraw funds on the other end of the bridge. Another example is Portal Token Bridge built on top of Wormhole (a message passing protocol) where the validation process takes place in an external network called the Guardian Network. The Polygon bridge, for example, has 100 validators, so compromising it would require compromising at least 51 of these validators, a difficult task due to the participants having their own native tokens at stake.