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The type of bridge used can vary based on its purpose, such as token bridges, NFT bridges, governance bridges, lending bridges, and ENS bridges. Without interoperability, the assets would be fragmented resulting in isolated chains with limited use cases. Users can then make the choice to use a specific bridge depending on their needs and informed compromise on different levels of security. Certain risks are unique to specific bridge designs and moreover the risks for one type of user may not be the same for another type of user.

🔵 ZK-Enabled Privacy

If a challenge is made, and a node attempts to censor it, users can force the node to post on Layer 1 and ensure the transaction is included on Layer 2. Security in this model relies heavily on the nodes challenging transactions and requires the use of bots and monitoring scripts to ensure security and prevent collusion amongst node operators. This is a type of bridge where 1-of-N watchers can prove fraud within a delay window. Another example includes NEAR Rainbow bridge (disregarding an Optimistic component related to the complexity of validating NEAR sig scheme there). In this case, the light clients only validate that majority of the consensus on the source chain attests to the transaction.
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).

• The main difference between the industry-led approaches and zkbridge is that the trust assumption is basically reduced to the existence of one honest node in the relay network, and that the zk-SNARK is sound.
• Audits and formally verifying smart contracts have become the focus, while private key management and conventional security, in general, has been left on the backburner.
• Suppose the validators of a source chain in IBC collude to submit a fraudulent transaction then the destination chain on IBC will still accept the transaction as the bridge only verifies that the source chain consensus was achieved.
• ’ In many cases upgrading the smart contracts of a messaging layer to fix bugs, improve speed, or launch new technology can introduce risk vectors that can compromise the security of the bridges and dApps using the messaging layer.
• The evidence is created using off-chain computation, which includes constructing circuits to verify the validators and their signatures and then generating the SNARK proof.
• Decentralized validation is the most secure, but also the most complex to build, whereas centralized validation is less secure but easier to build.

Bridging the Multichain Universe with Zero Knowledge Proofs

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.
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.

zkbridge (Berkeley RDI)

• The quickest way to compromise economic security is by stealing the private keys of the validators (i.e. the signer keys).
• Coinchange and its Research department are happy to share their fifth Research Report titled “Crosschain interoperability and security – Categorization and solutions”.
• The sooner the response, the higher the chances of recovering funds.
• The motivation is that a circuit for verifying N signatures essentially consists of N copies of identical sub-circuits, known as a data-parallel circuit, with each sub-circuit mutually exclusive from the rest.
• If qualified talent can be found from reputable organizations such as banks or tech companies that prioritize security, the centralized bridge can be as secure as possible.
• The core component of a Virgo prover is based on a zero knowledge extension of the GKR protocol which runs sum check arguments for each sub-circuit in the layered circuit and a polynomial commitment scheme.

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.

0 What Can Be Done Moving Forward To Analyze and Mitigate Bridge Risks?

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.
As bridges typically only support a limited set of tokens, bridge aggregators also incorporate DEXs and DEX aggregators, expanding the range of assets available for exchange across chains. People use liquidity network based token bridges for faster transfers by bypassing the native bridge’s delay. Hence, some token bridges can also have another layer called ‘liquidity networks’ on top of the message based bridge. While Mint and Burn bridges are beneficial in terms of user experience, they do not provide the same level of security as liquidity-based bridges.
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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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.
Unlike the other two industry-led ZKP bridge constructions, zkbridge is a framework on top of which several applications can be built. Electronlabs have proposed to parallelize the computation with multiple machines to generate proofs at the same rate as the block production rate and do a recursion to generate a single zk-Snark proof. The out of field modular arithmetic is a valuable optimization for the verification computation onchain.
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.
Ethereum was launched a few years later as the faster, more efficient blockchain compared to Bitcoin. Bitcoin was the world’s first and oldest public, permissionless blockchain meant to facilitate peer to peer transfer without the need for an intermediary. Blockchains are becoming increasingly important as a tool for managing and controlling digital assets. Threat response is still an important part of any security strategy as even with the best threat mitigation measures in place, it is still possible for a hack to occur. Decentralized validation is the most complex to build and can be done through a natively verified bridge or an optimistically verified bridge.
’ In many cases upgrading the smart contracts of a messaging layer to fix bugs, improve speed, or launch new technology can introduce risk vectors that can compromise the security of the bridges and dApps using the messaging layer. This problem seems to get worse as the bridges try to expand to newer and less proven blockchains making them the target for attackers. 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. The main challenge with bridge validation is that blockchains are designed to be consistent and validatable. In our conversations with security engineers from Hacken, it was evident that many notable bridges, specifically the ones utilizing external verification, prioritize smart contract security over conventional ones.
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 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.

For instance, in MetaMask Bridges, crosschain transfers are executed through two bridge aggregation protocols, LI.FI and Socket. Instead, the bridge aggregation protocols are integrated into a dApp's crosschain service spinmaya casino bonus offering. Although this component is centralized, it is crucial as quotes and routes for bridges are only available off-chain. To assist with this decision, aggregators offer a platform for users to compare different bridges and select the one that fits their requirements the best.