arXiv subjects

Kushal Babel

Publications and source records attributed to Kushal Babel.

12 recordsLinked to original sources

arXiv2026

Cadence: Extreme Pipelining with Multiple Concurrent Proposers

We present Cadence, a Byzantine fault-tolerant multi-proposer consensus protocol with arbitrarily low block intervals, optimal resilience, and optimal fast-path latency. Cadence divides time into equally spaced slots, one block per slot, each finalized in its own consensus instance. Blocks do not build directly on their predecessor, so instances run independently and none waits for an earlier block to finish or propagate; we call this extreme pipelining, decoupling the block interval from network latency. Cadence also removes the single-leader monopoly over transaction inclusion and ordering: under multiple concurrent proposers (MCP), several validators propose for each block, and it guarantees that, under synchrony, a transaction a correct proposer includes cannot be censored or deferred (short-term censorship resistance), and that no proposer can craft its proposal in reaction to the others' (hiding). To realize extreme pipelining, we introduce a general framework that turns any one-shot consensus meeting our slot-consensus specification into a multi-shot protocol. We instantiate it for MCP with two protocols of our own: Chorus, a slot consensus whose fast path finalizes a block in an optimal three rounds, with speculative finality one round earlier, and Conductor, an orchestrator that opens slots at an even cadence, more slowly under asynchrony to keep open slots bounded. To our knowledge, Cadence is the first MCP protocol to provide short-term censorship resistance and hiding at the fast-path latency of single-leader consensus. We prove safety, liveness, censorship resistance, and hiding under partial synchrony with optimal resilience (n = 3f+1). In simulation over Monad's 200 validators with five proposers per slot, finalization averages 219 ms (167 ms to speculative finality); at a 100 ms block interval a transaction waits on average 50 ms to enter a proposal.

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arXiv2026

EVM Workloads in the Wild: Evidence for Multi-Dimensional Gas Metering, State Growth, Delayed Execution, and Parallelism

Gas metering on EVM-compatible blockchains assumes that execution conditions are stable: that the resource mix is constant enough to justify collapsing execution costs into a single scalar with fixed relative prices, and that state drift between submission and execution does not materially alter a transaction's outcome. We measure the extent to which this assumption fails. We present a trace-level measurement study of EVM workloads on Ethereum (L1) and Base (L2) throughout 2025, sampling 3,000 blocks per day per chain. We decompose each transaction into opcode-level execution gas, intrinsic gas, refunds, and persistent state deltas. To measure state sensitivity, we re-execute transactions from September 2025 on older states and record how gas usage and storage access patterns change. We find the resource mix to be far from stable: on Base, storage reads and compute account for 29.2% and 24.3% of execution gas, while Ethereum devotes 34.9% to storage writes. Ethereum's gas limit doubling during 2025 shifted its own profile toward compute-heavier, Base-like patterns. Base also exhibits a higher fraction of cold storage reads (49.7% versus 39.6% on Ethereum). Persistent state growth, a permanent cost priced as a transient one, reaches 435 GB on Base versus 30 GB on Ethereum. Execution outcomes are equally unstable: gas estimates vary across nearby historical states for 46.0% of transactions on Base, compared to 13.9% on Ethereum, with especially high sensitivity for MEV and DeFi activity. Storage access patterns also diverge across states, limiting the effectiveness of access lists and complicating parallel execution. Our work provides an empirical foundation for multi-dimensional gas metering and explicit pricing of state growth. It shows that state-sensitive execution behavior complicates workload estimation, directly affecting transaction predictability and user experience.

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arXiv2026

Blockspace Under Pressure: An Analysis of Spam MEV on High-Throughput Blockchains

On high-throughput, low-fee blockchains, a qualitatively new form of maximal extractable value (MEV) has emerged: searchers submit large volumes of speculative transactions, whose profitability is resolved only at execution time. We refer to this as spam MEV. On major rollups, it can at times consume more than half of block gas, even though only a small fraction of probes ultimately results in a trade. Despite growing awareness of this phenomenon, there is no principled framework for understanding how blockchain design parameters shape its prevalence and impact. We develop such a framework, modeling spam transactions competing for on-chain opportunities under a competitive equilibrium that drives their profits to zero, and deriving equilibrium spam volumes as a function of block capacity, minimum gas price, and the transaction fee mechanism. Empirical evidence from Base and Arbitrum supports the model: spam grew sharply as block capacity was scaled up and fell when minimum gas prices were introduced. Our analysis yields three main insights. First, spam is always costly: when block capacity is scarce, it displaces users and drives up gas prices; as block capacity grows, it increasingly consumes execution resources, raising network externality, i.e., the cost of provisioning and processing blocks. We show that spam takes an increasing share of each additional unit of block capacity, so capping it before all users are included creates a favorable trade-off: forgoing a small amount of user welfare eliminates disproportionate spam and externality. Second, we extend the analysis to priority fee ordering and show that ordering transactions by gas price helps reduce spam, as spammers must pay more to reach early block positions. Third, as user demand grows and blockspace is scaled accordingly, spam's share of block capacity plateaus rather than growing indefinitely.

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arXiv2025

Timing Games in Responsive Consensus Protocols

Optimistic responsiveness -- the ability of a consensus protocol to operate at the speed of the network -- is widely used in consensus protocol design to optimize latency and throughput. However, blockchain applications incentivize validators to play timing games by strategically delaying their proposals, since increased block time correlates with greater rewards. Consequently, it may appear that responsiveness (even under optimistic conditions) is impossible in blockchain protocols. In this work, we develop a model of timing games in responsive consensus protocols and find a prisoner's dilemma structure, where cooperation (proposing promptly) is in the validators' best interest, but individual incentives encourage validators to delay proposals selfishly. To attain desirable equilibria, we introduce dynamic block rewards that decrease with round time to explicitly incentivize faster proposals. Delays are measured through a voting mechanism, where other validators vote on the current leader's round time. By carefully setting the protocol parameters, the voting mechanism allows validators to coordinate and reach the cooperative equilibrium, benefiting all through a higher rate-of-reward. Thus, instead of responsiveness being an unattainable property due to timing games, we show that responsiveness itself can promote faster block proposals. One consequence of moving from a static to dynamic block reward is that validator utilities become more sensitive to latency, worsening the gap between the best- and worst-connected validators. Our analysis shows, however, that this effect is minor in both theoretical latency models and simulations based on real-world networks.

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arXiv2025

Voting-Bloc Entropy: A New Metric for DAO Decentralization

Decentralized Autonomous Organizations (DAOs) use smart contracts to foster communities working toward common goals. Existing definitions of decentralization, however -- the 'D' in DAO -- fall short of capturing the key properties characteristic of diverse and equitable participation. This work proposes a new framework for measuring DAO decentralization called Voting-Bloc Entropy (VBE, pronounced ''vibe''). VBE is based on the idea that voters with closely aligned interests act as a centralizing force and should be modeled as such. VBE formalizes this notion by measuring the similarity of participants' utility functions across a set of voting rounds. Unlike prior, ad hoc definitions of decentralization, VBE derives from first principles: We introduce a simple (yet powerful) reinforcement learning-based conceptual model for voting, that in turn implies VBE. We first show VBE's utility as a theoretical tool. We prove a number of results about the (de)centralizing effects of vote delegation, proposal bundling, bribery, etc. that are overlooked in previous notions of DAO decentralization. Our results lead to practical suggestions for enhancing DAO decentralization. We also show how VBE can be used empirically by presenting measurement studies and VBE-based governance experiments. We make the tools we developed for these results available to the community in the form of open-source artifacts in order to facilitate future study of DAO decentralization.

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arXiv2025

MonadBFT: Fast, Responsive, Fork-Resistant Streamlined Consensus

This paper introduces MonadBFT, a novel Byzantine Fault Tolerant (BFT) consensus protocol that advances both performance and robustness. MonadBFT is implemented as the consensus protocol in the Monad blockchain. As a HotStuff-family protocol, MonadBFT has linear message complexity in the common case and is optimistically responsive, operating as quickly as the network allows. A central feature of MonadBFT is its tail-forking resistance. In pipelined BFT protocols, when a leader goes offline, the previous proposal is abandoned. Malicious leaders can exploit this tail-forking behavior as a form of Maximal Extractable Value (MEV) attack by deliberately discarding their predecessor's block, depriving that proposer of rewards and enabling transaction reordering, censorship or theft. MonadBFT prevents such tail-forking attacks, preserving both fairness and integrity in transaction execution. Another related feature of MonadBFT is its notion of speculative finality, which enables parties to execute ordered transactions after a single round (i.e., a single view), with reverts occurring only in the rare case of provable leader equivocation. This mechanism reduces user-perceived latency. Additionally, we introduce the leader fault isolation property, which ensures that the protocol can quickly recover from a failure. To our knowledge, no prior pipelined, leader-based BFT consensus protocol combines all of these properties in a single design.

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arXiv2024

Liquefaction: Privately Liquefying Blockchain Assets

Inherent in the world of cryptocurrency systems and their security models is the notion that private keys, and thus assets, are controlled by individuals or individual entities. We present Liquefaction, a wallet platform that demonstrates the dangerous fragility of this foundational assumption by systemically breaking it. Liquefaction uses trusted execution environments (TEEs) to encumber private keys, i.e., attach rich, multi-user policies to their use. In this way, it enables the cryptocurrency credentials and assets of a single end-user address to be freely rented, shared, or pooled. It accomplishes these things privately, with no direct on-chain traces. Liquefaction demonstrates the sweeping consequences of TEE-based key encumbrance for the cryptocurrency landscape. Liquefaction can undermine the security and economic models of many applications and resources, such as locked tokens, DAO voting, airdrops, loyalty points, soulbound tokens, and quadratic voting. It can do so with no on-chain and minimal off-chain visibility. Conversely, we also discuss beneficial applications of Liquefaction, such as privacy-preserving, cost-efficient DAOs and a countermeasure to dusting attacks. Importantly, we describe an existing TEE-based tool that applications can use as a countermeasure to Liquefaction. Our work prompts a wholesale rethinking of existing models and enforcement of key and asset ownership in the cryptocurrency ecosystem.

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arXiv2024

PROF: Protected Order Flow in a Profit-Seeking World

Users of decentralized finance (DeFi) applications face significant risks from adversarial actions that manipulate the order of transactions to extract value from users. Such actions -- an adversarial form of what is called maximal-extractable value (MEV) -- impact both individual outcomes and the stability of the DeFi ecosystem. MEV exploitation, moreover, is being institutionalized through an architectural paradigm known Proposer-Builder Separation (PBS). This work introduces a system called PROF (PRotected Order Flow) that is designed to limit harmful forms of MEV in existing PBS systems. PROF aims at this goal using two ideas. First, PROF imposes an ordering on a set ("bundle") of privately input transactions and enforces that ordering all the way through to block production -- preventing transaction-order manipulation. Second, PROF creates bundles whose inclusion is profitable to block producers, thereby ensuring that bundles see timely inclusion in blocks. PROF is backward-compatible, meaning that it works with existing and future PBS designs. PROF is also compatible with any desired algorithm for ordering transactions within a PROF bundle (e.g., first-come, first-serve, fee-based, etc.). It executes efficiently, i.e., with low latency, and requires no additional trust assumptions among PBS entities. We quantitatively and qualitatively analyze incentive structure of PROF, and its utility to users compared with existing solutions. We also report on inclusion likelihood of PROF transactions, and concrete latency numbers through our end-to-end implementation.

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arXiv2023

DAO Decentralization: Voting-Bloc Entropy, Bribery, and Dark DAOs

Decentralized Autonomous Organizations (DAOs) use smart contracts to foster communities working toward common goals. Existing definitions of decentralization, however-the 'D' in DAO-fall short of capturing key properties characteristic of diverse and equitable participation. We propose a new metric called Voting-Bloc Entropy (VBE, pronounced ''vibe'') that formalizes a broad notion of decentralization in voting on DAO proposals. VBE measures the similarity of participants' utility functions across a set of proposals. We use VBE to prove a number of results about the decentralizing effects of vote delegation, proposal bundling, bribery, and quadratic voting. Our results lead to practical suggestions for enhancing DAO decentralization. One of our results highlights the risk of systemic bribery with increasing DAO decentralization. To show that this threat is realistic, we present the first practical realization of a Dark DAO, a proposed mechanism for privacy-preserving corruption of identity systems, including those used in DAO voting. Our Dark-DAO prototype uses trusted execution environments (TEEs) in the Oasis Sapphire blockchain for attacks on Ethereum DAOs. It demonstrates that Dark DAOs constitute a realistic future concern for DAO governance.

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arXiv2023

Mysticeti: Reaching the Limits of Latency with Uncertified DAGs

We introduce Mysticeti-C, the first DAG-based Byzantine consensus protocol to achieve the lower bounds of latency of 3 message rounds. Since Mysticeti-C is built over DAGs it also achieves high resource efficiency and censorship resistance. Mysticeti-C achieves this latency improvement by avoiding explicit certification of the DAG blocks and by proposing a novel commit rule such that every block can be committed without delays, resulting in optimal latency in the steady state and under crash failures. We further extend Mysticeti-C to Mysticeti-FPC, which incorporates a fast commit path that achieves even lower latency for transferring assets. Unlike prior fast commit path protocols, Mysticeti-FPC minimizes the number of signatures and messages by weaving the fast path transactions into the DAG. This frees up resources, which subsequently result in better performance. We prove the safety and liveness in a Byzantine context. We evaluate both Mysticeti protocols and compare them with state-of-the-art consensus and fast path protocols to demonstrate their low latency and resource efficiency, as well as their more graceful degradation under crash failures. Mysticeti-C is the first Byzantine consensus protocol to achieve WAN latency of 0.5s for consensus commit while simultaneously maintaining state-of-the-art throughput of over 200k TPS. Finally, we report on integrating Mysticeti-C as the consensus protocol into the Sui blockchain, resulting in over 4x latency reduction.

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arXiv2022

SHORTSTACK: Distributed, Fault-tolerant, Oblivious Data Access

Many applications that benefit from data offload to cloud services operate on private data. A now-long line of work has shown that, even when data is offloaded in an encrypted form, an adversary can learn sensitive information by analyzing data access patterns. Existing techniques for oblivious data access-that protect against access pattern attacks-require a centralized and stateful trusted proxy to orchestrate data accesses from applications to cloud services. We show that, in failure-prone deployments, such a centralized and stateful proxy results in violation of oblivious data access security guarantees and/or system unavailability. We thus initiate the study of distributed, fault-tolerant, oblivious data access. We present SHORTSTACK, a distributed proxy architecture for oblivious data access in failure-prone deployments. SHORTSTACK achieves the classical obliviousness guarantee--access patterns observed by the adversary being independent of the input--even under a powerful passive persistent adversary that can force failure of arbitrary (bounded-sized) subset of proxy servers at arbitrary times. We also introduce a security model that enables studying oblivious data access with distributed, failure-prone, servers. We provide a formal proof that SHORTSTACK enables oblivious data access under this model, and show empirically that SHORTSTACK performance scales near-linearly with number of distributed proxy servers.

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arXiv2021

Clockwork Finance: Automated Analysis of Economic Security in Smart Contracts

We introduce the Clockwork Finance Framework (CFF), a general purpose, formal verification framework for mechanized reasoning about the economic security properties of composed decentralized-finance (DeFi) smart contracts. CFF features three key properties. It is contract complete, meaning that it can model any smart contract platform and all its contracts--Turing complete or otherwise. It does so with asymptotically constant model overhead. It is also attack-exhaustive by construction, meaning that it can automatically and mechanically extract all possible economic attacks on users' cryptocurrency across modeled contracts. Thanks to these properties, CFF can support multiple goals: economic security analysis of contracts by developers, analysis of DeFi trading risks by users, fees UX, and optimization of arbitrage opportunities by bots or miners. Because CFF offers composability, it can support these goals with reasoning over any desired set of potentially interacting smart contract models. We instantiate CFF as an executable model for Ethereum contracts that incorporates a state-of-the-art deductive verifier. Building on previous work, we introduce extractable value (EV), a new formal notion of economic security in composed DeFi contracts that is both a basis for CFF and of general interest. We construct modular, human-readable, composable CFF models of four popular, deployed DeFi protocols in Ethereum: Uniswap, Uniswap V2, Sushiswap, and MakerDAO, representing a combined 24 billion USD in value as of March 2022. We use these models along with some other common models such as flash loans, airdrops and voting to show experimentally that CFF is practical and can drive useful, data-based EV-based insights from real world transaction activity. Without any explicitly programmed attack strategies, CFF uncovers on average an expected $56 million of EV per month in the recent past.

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