The L1 Weekly Report is published every Friday, focusing on the development of Layer 1 blockchains. If you have any suggestions, feel free to contact [email protected].

Bitcoin

• Bitcoin node P2P traffic analysis
  • The author shares recent node traffic analyses initially done for Erlay’s bandwidth savings, describing a method to estimate TCP/IP traffic using tracepoints. After validating the method with around 1% average error, the estimates can be used to break down traffic by message type, payload/overhead, connection types, and per-peer traffic. This helps assess optimizations and understand P2P network dynamics, and reveals types of incoming nodes like IBD, regular, and spy nodes. The author offers to visualize more data and provides Jupyter notebooks on GitHub with some grouped data.
• Disclosure: LND Excessive Failback Exploit
  • Keeping specifications up-to-date can improve security for all implementations.
  • Update to at least LND 0.18.0 to protect your funds.
• Bitcoin Recursive Autonomous Intelligence Network
  • This paper presents B.R.A.I.N., a decentralized framework enabling autonomous financial operations on Bitcoin’s UTXO model without custodial intermediaries or cross - chain bridges. It formalizes a recursive UTXO state management system with provable termination, implements non - interactive zero - knowledge verification for yield attestation, and applies Merkle path verification for secure inter - agent communication while preserving transaction graph privacy. Empirical analysis shows its viability under varying network conditions. Experimental implementations on Bitcoin’s signet testing environment achieved an annualized yield of about 3.8%, maintaining full node verification and sovereignty. It builds on foundational Bitcoin research and recent script optimizations, aiming to contribute to the development of decentralized finance on the Bitcoin blockchain.

Ethereum

• Blob Aggregation - Step Towards More Efficient Blobs
  • This article discusses the problem of limited and underutilized blob space in rollups. It proposes blob aggregation, which combines multiple rollups’ blobs into one to share the space, reduce costs, and improve efficiency. The solution involves new concepts like blob shards and aggregators. However, there are open questions regarding incentives, blob shard collisions, and potential exploits. Overall, it aims to enhance rollup efficiency and make blob space more affordable.
• Delayed Execution Design Tradeoffs
  • This article explores three delayed execution designs in Ethereum. It explains EIP - 7862, EIP - 7886, and EIP - 7732, each with its own approach to delayed execution. The article then analyzes how these designs impact properties like block preparation time, propagation time, and verification time. It also assesses their implementation complexities. Overall, it aims to understand the trade - offs in these designs rather than presenting them as competing options.
• Doubling the blob count with Gossipsub v2.0
  • This article introduces Gossipsub v2.0, which doubles Ethereum’s blob capacity by reducing bandwidth usage through a lazy-pull mechanism. By replacing full-message broadcasts with announcement/request signals (IANNOUNCE/INEED), it nearly eliminates duplicates while maintaining propagation efficiency. Simulations show v2.0 handles 32 messages within 4 seconds (vs. 16 in v1.2), though larger messages still face delays. Key tradeoffs include balancing propagation speed with timeout settings and addressing malicious peers ignoring requests. The approach significantly improves scalability for high-volume blob propagation.
• Sealed transactions
  • This article proposes a “sealed transactions” mechanism to protect Ethereum transactions from MEV extraction without relying on trusted third parties. Users broadcast encrypted transaction commitments with a top-of-block fee, which are validated in a subsequent block after they reveal the actual transaction. Attesters enforce correct ordering based on fees, enhancing trustlessness and censorship resistance. However, challenges include user complexity, potential delays, and ensuring timely reveals. The approach balances trade-offs between trustlessness and practical usability compared to threshold encryption-based solutions like Shutter.
• Preconfirmation Fair Exchange
  • This article introduces a framework to analyze timely fair exchange (TFE) protocols for transaction preconfirmations in Ethereum, focusing on enforcement mechanisms and overseer roles. It categorizes TFE solutions based on punishment effectiveness (e.g., slashing, orderflow loss) and liveness dependency on overseers. The framework highlights that repeated-game preconfirmers (e.g., L2 sequencers) with informal user monitoring achieve optimal TFE guarantees, while L1 solutions face challenges due to one-shot proposers. Existing protocols like Mev-commit and Espresso are evaluated, and L1 gateway designs are discussed with warnings about centralization risks. The conclusion emphasizes guardrails like inclusion lists and formal overseers to mitigate L1 monopolization, while L2s benefit from aligned governance-elected overseers.
• Towards safe optimization the storage related gas cost
  • This article identifies three inconsistencies in Ethereum’s storage gas pricing, such as charging disk access fees for cached data in the same block or across 128 blocks, and redundant costs for duplicate contract deployments. It proposes four optimizations (O1-O4) to align gas fees with actual memory/disk accesses, including reduced fees for cached reads and deduplicated contract storage. Evaluations show these optimizations reduce transaction fees by 32% (5.6M USD weekly savings), outperforming EIP-2929 by nearly three times. The framework ensures compatibility with Ethereum’s consensus and addresses challenges like cache synchronization and contract bytecode reuse.
• AI as the engine, humans as the steering wheel
  • This article proposes a governance model where AI acts as an efficient “engine” for decision-making, while humans provide high-quality directional input as the “steering wheel.” It introduces mechanisms like Futarchy (prediction markets aligned with human values), Distilled Human Judgement (using small jury inputs to guide AI models), and Deep Funding (credit allocation through dependency graphs). These systems aim to combine AI’s computational power with human oversight, avoiding centralization risks and leveraging open markets for innovation. The approach emphasizes credible neutrality, scalability, and incentive alignment, positioning it as a viable framework for future decentralized governance.
• Decentralized Random Block Proposal: Eliminating MEV and Fully Democratizing Ethereum
  • This article presents a new decentralized random block proposal system for Ethereum. It intends to get rid of block - level MEV and make the block - proposing process fully democratic. In contrast to the current Proposer - Builder Separation (PBS) model, where around 80% of blocks are controlled by two major entities, this system enables all Ethereum clients to generate blocks through a random algorithm that combines RANDAO and VDF. By doing so, it eliminates the profit - driven manipulation of transaction order and distributes the power of block - building among thousands of clients.