Papers for
blockchain developers
Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.
Privacy flaws create value gaps in crypto protocols and markets
Pricing the Unprovable: Ambiguity, Turnstile Runs, and the Verifiability Discount in Crypto Protocols
Abstract: Privacy-preserving protocols can repair a vulnerability without establishing whether it was exploited beforehand, even when no theft is reported and aggregate supply is protected. We call the potential value reduction from this gap the verifiability discount. A turnstile model shows how early withdrawal can shift a possible shortfall to remaining holders and why credible evidence can become more valuable as exposure grows. We introduce VDISC, a reproducible framework that records reported loss, exposed value, public evidence, returns, and pool flows separately. It combines Orchard's staged disclosures with reconstructed on-chain flows, earlier Zcash cases, and a 40-event security panel. Orchard follows the predicted direction: market responses were muted after repair and supply assurance, while the largest negative return and aggregate shielded-pool net outflow aligned with the acknowledgment that past abuse could not be ruled out. These patterns are directional, not causal. Across events, market-cap-normalized reported loss and unresolved exposure overlap among the 38 events with a public loss figure (Pearson 0.86, Spearman 0.56), partly because exposure is often coded from the loss itself, so returns alone cannot distinguish reported loss from unresolved history. The findings motivate three candidate design priorities: produce privacy-compatible evidence about past states, limit the state exposed by a single flaw, and disclose residual uncertainty explicitly.
Tulva enables practical asynchronous threshold fully homomorphic encryption
Tulva: Practical Asynchronous Threshold FHE
Abstract: We present Tulva, a practical threshold FHE scheme which equips a base FHE scheme with an asynchronous threshold decryption mechanism in a modular way. Our scheme simultaneously (1) is compatible with virtually any base FHE scheme and leaves its ciphertexts unchanged apart from an appended random tag, (2) supports a wide range of threshold profiles $(t,K)$ and ring degrees $\geq 256$ with 6-25 bits partial decryption per plaintext bit, and (3) achieves security in the presence of partial decryption queries on challenge ciphertexts based on the standard LWE assumption. We provide an open-source implementation, benchmark its threshold decryption performance and evaluate the end-to-end costs for typical privacy-preserving Ethereum Virtual Machine (EVM) use cases. For 16-out-of-512 threshold and a publicly preprocessed ciphertext, computing secret-dependent partial decryption and public share combination requires only 3.7 ms and 0.5 ms, respectively, on commodity hardware. Compared with the state-of-the-art synchronous scheme [Zyskind et al., CCS'25], we replace their ciphertext-independent yet interactive preparation of secret-correlated randomness with a public, ciphertext-dependent 0.5 s preprocessing step, eliminate interaction in the online phase while maintaining similar decryption time on the same machine, and support 32$\times$ more total users.
Quantum resistant protocol secures peer to peer energy trading networks
Quantum-Resilient Secure Protocol for Decentralized Edge-IoT Peer-to-Peer Energy Trading Systems
Abstract: The rise of quantum computing presents substantial challenges to the security of Peer-to-Peer (P2P) energy trading systems. This paper introduces an innovative mutual authenticated session key agreement protocol aimed at protecting edge-IoT P2P energy trading communications in the quantum era. Each peer is an IoT-enabled smart metering device that is registered by an edge registration authority and acts as both producer and consumer. The proposed protocol incorporates CRYSTALS-Kyber's quantum-resistant cryptographic suite to guarantee the authenticity and confidentiality of negotiated session keys in the presence of quantum threats. Furthermore, it leverages the Hedera Hashgraph public blockchain, which is recognized for its quantum-resilient design, to ensure transparency and support efficient revocation mechanisms. Extensive comparative analyses have been conducted to demonstrate the protocol's superiority over existing alternatives, including both traditional schemes based on classical cryptography and emerging early-stage post-quantum approaches, in terms of performance and security features. By combining robust security and high efficiency, the proposed protocol fosters the development of resilient decentralized energy markets, paving the way for secure and sustainable energy distribution in the future.
Large language models often produce flawed smart contracts despite compiling
SolBehave: Evaluating the Behavioural Correctness of LLM-Generated Smart Contracts
Abstract: Large language models increasingly generate Solidity smart contracts that, once deployed, can never be patched, making a single latent fault permanent and exploitable. Yet current evaluations mostly ask only whether generated code compiles. We introduce SolBehave, a benchmark for evaluating the correctness of model-generated contracts at scale, moving beyond ad hoc unit tests. Across 250 real, reproducible Ethereum contracts, we apply three complementary tests of behavioural fidelity: differential fuzzing, historical-transaction replay, and, as our core contribution, synthetic-transaction replay guided by a Dynamic Condition Response (DCR) graph that enumerates the space of legitimate function-call sequences. Differential fuzzing compares each generated function with the original on automatically generated inputs; historical replay compares the whole contract on the transactions it actually received on-chain; DCR-guided replay compares it on sequences of calls that follow its intended usage, including orderings that never occurred on-chain. We evaluate seven state-of-the-art open-weight models after one round of automated repair. Compilation success ranges from 26.4% to 92.7%, but under differential fuzzing only 31.4% of all generated function bodies that compile, pooled over models and samples, are equivalent to the original. Divergence at the contract level is the norm rather than the exception: for six of the seven models, between 13% and 31% of the generated contracts that compile diverge from the original under historical replay, and between 13% and 44% under DCR-guided replay; only Gemma-4-31B stays below 3% on both. Compilation is therefore a necessary condition for correctness and far from a sufficient one.
Soliduzz finds smart contract compiler bugs using assertion checks
Soliduzz: Finding Miscompilations in Smart-Contract Compilers with Assertion-Driven Equivalence Oracles
Abstract: Smart contracts compiled to the Ethereum Virtual Machine (EVM) can manage high-value assets and are difficult to patch after deployment. Compiler miscompilations are therefore especially dangerous: compilation succeeds, but the generated bytecode does not preserve the semantics of the source program. Existing smart-contract compiler fuzzers either focus on robustness failures or rely on differential oracles that compare compiler configurations. We present Soliduzz, an approach for finding miscompilations in EVM smart-contract compilers using assertion-driven equivalence oracles. Soliduzz uses product programs to encode semantic equivalence as executable assertions. The key shift is to compile these self-checking programs and let off-the-shelf fuzzers and symbolic execution engines explore the resulting bytecode for assertion violations, without requiring compiler-specific support from the analyzer. Soliduzz instantiates this idea with two complementary families of metamorphic transformations. The first starts from equivalent expressions and lifts them into smart-contract code that deliberately exercises EVM-specific features such as storage, data locations, control flow, contract interactions, and inline assembly. The second generalizes Equivalence Modulo Inputs (EMI) from fixed concrete inputs to symbolic input spaces. Our symbolic EMI records coverage in the original computation and uses it to guard mutations in the transformed computation. Together, these transformations produce product programs that assert that paired computations yield the same outputs. We evaluate Soliduzz on three EVM smart-contract compilers (solc, solx, and vyper) using several analysis tools. Overall, Soliduzz exposes 29 bugs. Of these, 24 are compiler bugs: 6 miscompilations, 17 internal compiler errors, and 1 hang. The remaining 5 are bugs in the analysis tools.
AgentValve secures payment authorization against fake identities in AI markets
AgentValve: Sybil-Resilient Payment Authorization for Permissionless AI Markets
Abstract: AI agents increasingly select and pay service providers without human review. In emerging permissionless markets, however, adversaries can create inexpensive identities and fabricate feedback to inflate provider reputation, making reputation-based payment authorization vulnerable to Sybil attacks and exposing clients to unbounded financial loss. This paper presents AgentValve, a protocol for Sybil-resilient payment authorization in permissionless AI markets. AgentValve builds on a trust network that represents reputation as finite capacity in a directed graph and authorizes payments through trust paths with sufficient available capacity. A smart contract atomically reserves the capacity supporting each admitted payment, bounding honest agents' payment exposure by the capacity they extend into the adversarial region, and thus creating identities or interactions entirely within that region cannot increase this bound. To limit capacity depletion by malicious senders, AgentValve combines payment-backed capacity creation with bounded route length, preventing attackers from depleting honest capacity without incurring corresponding payment costs. AgentValve further decouples off-chain route discovery from on-chain verification and introduces a witness-commit mechanism that reduces route verification to linear work while requiring only constant persistent state per admitted payment. We implement a AgentValve prototype and evaluate it using six months of Ethereum data and synthetic workloads. Experimental results show that under attacks with up to 10,000 synthetic Sybil identities and with chosen attackers, the payment exposure and capacity depletion remain bounded. Regarding practicality, the witness-commit mechanism lowers admission cost by up to 40.8% compared with baselines, and admitting common payments costs approximately \$0.04-\$0.21.
Bitcoin oracle use tracked but many records missing or incomplete
On-Chain Archaeology of Bitcoin Oracles: Evidence of Use under Limited Observability
Abstract: Before Ethereum made the "oracle problem" a household term, Bitcoin already had oracles serving as feeds, key-release services, federated signers, and arbiters that carried real value on the main chain. This study traces their use and the changing evidence of oracle activity from early days through July 2026. We combine a complete census of Counterparty betting (1,149 bets), analysis of the full Bitcoin chain through block 958,628, and searches for documented keys from Reality Keys, Orisi, Bitrated, and Oraclize in an 854-million-row public-key index. We also recover DLC oracle records from an archived explorer and live Nostr relays. Two results emerge. First, early contracts remain on-chain, but many event descriptions have disappeared, and protocol encoding and API limitations complicate access to the surviving record. However, for modern DLCs, public oracle announcements can survive even when the contracts using them cannot be identified on-chain. In the script classes examined, the share of spends that reveal no script peaks at 81.9% in 2024 after excluding spends containing inscription data. Second, public registries can give a misleading picture of oracle use. In Counterparty, 95% of pre-2018 sources declaring an oracle fee were never bet on. In Bitrated, 0.1% of archived keys appear on-chain overall, compared with 10 of 19 keys captured in 2014. Sport dominates Counterparty's matched volume, while a daily price series dominates the archived DLC announcements. These findings show how protocol design and data preservation shape the historical record of Bitcoin oracle use.
Stronger simpler cryptographic hash functions using new math assumptions
Simple Extremely Lossy Functions from Small-Exponent Hashing
Abstract: Extremely Lossy Functions (ELFs) are a standard model primitive that captures many useful properties of random oracles (Zhandry, Crypto 2016). While there are many variations of ELFs with additional properties, every construction (excluding obfuscation) has followed essentially the same template of bootstrapping from a sequence of ELFs secure only against fixed-size adversaries, and every construction was based on only the exponential hardness of DDH (or $k$-Lin), an assumption that is only reasonable over elliptic curves. We introduce and construct Extremely Lossy Trapdoor Hashing (ELTDH), a stronger notion that implies all known variations of ELFs. Our construction achieves ELTDH in one go, without bootstrapping from schemes secure for only fixed-size adversaries, which makes it simpler and more efficient than existing ELFs. We assume exponential security of the small-exponent discrete logarithm, together with polynomial security of decisional composite residuosity (DCR). Exponential security is only required in the size of the secret exponent, not the size of the group, so the assumption plausibly holds for multiplication modulo $N^2$ (and for many other cryptographic groups), despite the subexponential-time discrete logarithm attacks from index calculus. Our results diversify the assumptions underlying ELFs, while also giving a simpler construction.
Optimizing reliable broadcast latency with improved step guarantees
Optimistic Reliable Broadcast in Three Steps
Abstract: We study the latency tradeoffs of signature-free asynchronous reliable broadcast with optimistic two-step delivery. We consider $n$ parties, of which at most $f$ are Byzantine. An optimistic fault budget $b\le f$ guarantees two-step delivery with an honest broadcaster and at most $b$ faults, while correctness tolerates $f$ faults. We write $(d_o,d_s,d_t)$ for optimistic latency, honest-broadcaster latency with up to $f$ faults, and totality delay-the elapsed time from first to last honest delivery. For $3f+1\le n<4f$, our first construction improves Opt-RBC's $(2,4,4)$ guarantees to $(2,3,4)$, preserving its maximal optimistic budget $b_*=\lfloor n/2\rfloor-f$. Thus maximal optimism is compatible with the optimal three-step good case. We prove a complementary lower bound: for $3f+1\le n<4f$, every deterministic reliable broadcast protocol in our asynchronous model with two-step optimistic budget $b\ge n-3f$ has totality delay at least three, even when the broadcaster is honest. Our second construction achieves $(2,3,3)$, matching this lower bound at maximal optimism when $f\ge2$ and $\lceil(10f-3)/3\rceil\le n<4f$. Both constructions use quadratic messages and tolerate adaptive corruption. In the matching range, maximal optimism therefore costs exactly one totality step relative to Bracha's $(3,3,2)$, without increasing good-case latency.
Decentralized agent workflows often fail to guarantee correct task outcomes
SoK: Decentralized Agent Economic Infrastructure
Abstract: Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately. This creates a simple problem: a workflow can look correct at each step and still produce the wrong outcome. For example, a correct escrow may release payment on an authorized approval that provides little evidence that the delivered work actually satisfied the task. We systematize this problem across the full lifecycle of an agent task. Our study organizes security and economic requirements into 17 property families over six stages, with receipt soundness and completeness assessed separately. We examine 12 systems and standards, five reusable mechanism families, and four classical baselines. We introduce guarantee closure, a task-relative criterion for determining whether guarantees established at one stage remain available and constrain the later decisions that depend on them. We apply the criterion to controlled and native workflows, covering 840 matched executions and an exhaustive 11,648-case check over a finite objective-task domain. Our results expose recurring failures between verification and settlement, where conforming work can remain unaccepted or valid evidence can be ignored. Public records and model judgments further distinguish recorded approval from evidence of task conformance, while economic analysis identifies the report, penalty, and shared-error assumptions behind these guarantees. These findings show where end-to-end guarantees fail and what must be repaired to preserve them across the workflow.
Device independent oblivious transfer works despite quantum device faults
Robust and leakage-resilient device-independent oblivious transfer in MiniQCryp
Abstract: Assuming post-quantum one-way functions, we construct device-independent (DI) oblivious transfer (OT) and bit commitment: honest parties use only trusted classical computation to operate untrusted quantum devices, which may share arbitrary entanglement and behave non-IID. Security is simulation-based against quantum polynomial-time adversaries and composes sequentially with efficient simulators. One protocol skeleton serves both, in two regimes. With isolated laboratories and coordinate-local measurements in the honest receiver's device, it tolerates a constant rate of honest-device faults. With polylogarithmically many qubits of adaptive leakage between the laboratories and arbitrary joint measurements, it tolerates an inverse-polylogarithmic rate. Each elementary DI call uses a fresh, isolated batch of polylogarithmically many device coordinates, and total device use in the compiled OT protocol is polynomial. The commitment has efficient simulators against both parties and yields DI coin tossing with abort. Because OT is complete for secure computation, the construction yields a DI protocol, with abort, for every efficiently computable classical functionality on a fixed number of parties, secure against static corruption of any proper subset of them. The commitment's extractor changes a public parity relation through classical equivocation and leaves the device execution, hence its leakage, unchanged. A commit-and-prove functionality, disjoint audits, and an affine consistency check link the certified correlations to ideal OT. Sender security rests on a selector-aware parallel-repetition bound for the Magic Square game, which we derive from the two-round threshold theorem of Kundu and Tan.
Xdc protocol enables cross-network messaging and asset settlement
XIM: The XDC Interledger Messaging Protocol
Abstract: Distributed ledgers, privacy-preserving institutional networks, and conventional payment systems increasingly need to exchange authenticated messages and settle assets across heterogeneous trust domains. Existing interoperability systems typically optimize for one of three concerns: application-level abstraction, cross-chain message transport, or synchronized execution within a related ledger family. This paper proposes XIM, the XDC Interledger Messaging Protocol, a chain-agnostic protocol for transporting canonical messages across heterogeneous networks while allowing each communication lane to select an explicit verification policy. XIM separates message semantics from transport, verification, execution, routing, asset identity, and compliance metadata. Its cryptographic state is represented by deterministic message identifiers and commitment roots, while an append-only transition log provides auditability and replay protection. XIM introduces a Universal Asset Identifier (UAID), a pluggable adapter interface, lane-scoped security policies, and an optional policy-aware route graph for multi-hop settlement. XDC Network can serve as a coordination and settlement domain without requiring every XIM message or route to transact through XDC. We specify the protocol model, state machine, message encoding, commitment structure, verification modes, failure semantics, security assumptions, threat model, implementation architecture, and an incremental deployment plan. The design targets public blockchains, permissioned ledgers, institutional networks, and authenticated financial-system gateways, with particular attention to stablecoins, tokenized assets, trade finance, and ISO 20022-compatible payment workflows.
Quantum protocol generates fully certified random bits without trusted seeds
Certified Randomness with Optimal Rate
Abstract: The generation of certified random bits is an emerging near-term application of quantum computers. Potential applications, such as randomness beacons and CRS generation, require nearly uniform randomness, whose rate (the ratio of min-entropy to bitlength) is ~ 1. However, existing protocols for certified randomness either produce weakly random strings with rate o(1), or they require a trusted random seed. We show how to certify randomness with the optimal rate ~ 1 without requiring any trusted randomness from the verifier. Our protocol is secure unconditionally in the quantum random oracle model (QROM). This improves the result of Coladangelo et al., who certified weakly random strings unconditionally in the QROM, and answers a question posed by Aaronson and Hung. We also define and construct a proof of conditional min-entropy, which certifies optimal min-entropy even conditioned on an adversarially chosen transcript. We show an application of this primitive to randomness beacons, where each pulse should have high min-entropy conditioned on all previous messages.
Homomorphic encryption improves error rates in quantum-safe interactive proofs
Tight Parallel Repetition for Private-Coin Arguments
Abstract: We show that assuming the existence of homomorphic encryption, parallel repetition of all interactive arguments (after being run under homomorphic encryption) reduces the soundness error at a tight exponential rate even in the post-quantum setting. Moreover, we generalize this result to hold for threshold verifiers, where the parallel repeated verifier accepts if and only if at least $t$ of the executions are accepted (for some threshold $t$). Prior to this work, these results were known only when the cheating prover was assumed to be classical, and it was not known how to achieve tight bounds. As a corollary, we construct the first constant-round succinct argument for $\mathsf{QMA}$ with negligible completeness and soundness errors assuming only the existence of quantum homomorphic encryption.
Quantum puzzles unlock time delays impossible classically
Quantum Time-Lock Puzzles in the Quantum Random Oracle Model
Abstract: A time-lock puzzle allows a sender to hide a message in a puzzle such that recovering the message requires substantially more sequential computation than the time required to generate the puzzle, even when parallel computation is allowed. Applications of time-lock puzzles include timed-release encryption, sealed-bid auctions, electronic voting, fair contract signing, coin flipping, and Byzantine consensus. However, time-lock puzzles are known to be impossible in the classical random oracle model. To overcome the classical barrier, in this work we consider quantum time-lock puzzles, in which the puzzle itself is a quantum state. Our construction in the quantum random oracle model achieves generation in one oracle round, solving in at most $T$ oracle rounds, and security against polynomial-width quantum adversaries of depth $o(T)$ for every polynomially bounded delay $T=T(λ)$, resolving an open problem posed by Mahmoody, Moran, and Vadhan (2011).
Byzantine causal reliable broadcast with constant message overhead
Byzantine Causal Reliable Broadcast with Constant Metadata Overhead
Abstract: Asynchronous Byzantine Reliable Broadcast (BRB) is a fundamental primitive that guarantees agreement and validity in distributed systems subject to Byzantine faults, but it lacks ordering guarantees. Causal message ordering is important for many applications such as blockchain and social networking. Existing solutions for Byzantine Causal Reliable Broadcast (BCRB) have several drawbacks. Such protocols typically append vector clocks or dependency barriers to application messages, resulting in a metadata overhead that scales linearly with $n$, the number of processes in the system. In this paper, we propose the first optimal message overhead BCRB algorithm that guarantees safety. We do this by re-engineering Bracha's BRB algorithm with relatively small but critical modifications, and prove that our algorithm solves BCRB with optimal message metadata. The algorithm achieves constant-size $\mathcal{O}(1)$ message metadata overhead and $\mathcal{O}(n^2)$ messages, resulting in $\mathcal{O}(n^2)$ communication word complexity. This is as against $\mathcal{O}(n^3)$ communication word complexity of existing protocols. The algorithm tolerates $f < n/3$ Byzantine processes, which is the well-known optimal resilience bound, and uses four phases.
Penalties must cover future losses to stop blockchain collusion
When One Leak Pays Forever: Context Binding and the Price of Deterring Collusion
Abstract: A coalition that deviates once can profit many times when what it sells keeps working. In a threshold-encrypted mempool, a leading defense against maximal extractable value (MEV), a quorum of the decryption committee that sells its decryption capability to a front-runner exposes every later block that the capability still decrypts. We ask how large a penalty, such as slashable stake, deters this kind of collusion. In our repeated game, a single leak by any coalition in a monotone family of authorized coalitions (for example, any $k$ of the $n$ committee members) unlocks a set of future rounds, costs a one-time penalty, and ends the coalition's participation. We show that every dynamic deviation reduces to choosing a leak time, so deterrence holds if and only if each coalition's penalty covers the largest discounted value that a single leak reaches. Without discounting, over $T$ rounds of unit value full reuse needs a penalty of $T$ while binding each leak to its own round needs $1$, so no penalty that is constant in the horizon deters unbounded reuse; a reuse window of $w$ rounds costs at most $w$ times the largest per-round value. The cheapest profile of per-party stakes that deters every coalition solves a covering linear program. For blockchain design, per-epoch keys cut the required stake from the value of a key's lifetime to the value of one epoch; we calibrate the gap on Ethereum front-running data and place Ferveo and Shutter in the model. The analysis extends to sealed-bid auctions, multi-authority voting, and federated learning under a shared key.
Analysis shows how Solana blockchain processes blocks and transactions
Analyzing Solana's Blocks and Transactions
Abstract: Solana is one of the most popular blockchains, and is arguably the most widely used blockchain for smart contracts, also known as dApps. Understanding the types of smart contracts that are being executed by Solana and their interplay is therefore highly beneficial both for designers of modern blockchains and developers of smart contracts. To that end, in this paper we analyze a million recent Solana blocks. We report statistics about the size of blocks (number of transactions per block), execution time units for individual transactions and fees, and invoked Solana programs. Further, based on the declared readset and writeset of each transaction, as mandated by Solana, we analyze the conflicts and corresponding conflict graphs arising within each block. These latter statistics are important to understand the potential for parallelism in the network, which is one of the main claimed benefits of Solana. The data and code are available in open source.
SmartMemory finds mismatches in smart contract off chain communication
SmartMemory: Detecting On-chain-off-chain Communication Inconsistency for Smart Contract via Memory-based Agent
Abstract: Smart contracts underpin decentralized finance, where growing demand for on-chain/off-chain communication(OFC) has driven diverse applications such as cross-chain bridges, real-world asset tokenization, and fiat-backed stablecoins. TheOFC-related security incidents in these applications are increasingly frequent, but prior studies address separate vulnerability categories within OFC applications rather than providing a unified view, causing vulnerabilities outside known patterns to be missed.In this paper, we identify OFC inconsistency (OFCI) as a root cause of OFC vulnerabilities, which arises from business-logic flaw and ultimately breaks the equivalence between the on-chain and off-chain asset representations to induce inconsistency.Automatically detecting OFCIs faces two challenges including (1)locating heterogeneous business logic, and (2) transferring existing vulnerability knowledge to identify unseen OFCI instances. To this end, we propose SmartMemory, the first framework to leverage a memory-based agent for OFCI detection. To address heterogeneity, SmartMemory maps diverse implementations ofOFC contracts into a canonical business-semantic representation to locate the business logic for OFCI inspection. For knowledge reuse, SmartMemory integrates a memory-based agent to distill vulnerability knowledge from features into patterns and detection rules, enabling knowledge transfer across cases to identify unseenOFCIs. Lastly, SmartMemory performs taint analysis to verify the reachability, type, and impact of each candidate OFCI. We construct the first real-world OFCI dataset comprising 48 DApps with 81 OFCIs for evaluation, on which SmartMemory achieves80.68% precision and 87.65% recall. In addition, through an analysis of 325 real-world OFC applications, SmartMemory detects 36 previously unknown OFCIs, all of which have been confirmed and fixed by corresponding parties.
Procedural neural decisions verified for gas-efficient blockchain use
Zero-Storage Procedural Neural Synthesis via Boundary Dynamics: Formal Verification in Lean 4 and Bare-Metal Gauntlet Validation
Abstract: Contemporary neural inference architectures rely on dense floating-point weight matrices stored in high-bandwidth memory (VRAM), incurring severe memory-wall bottlenecks and preventing native execution inside deterministic virtual machines like the Ethereum Virtual Machine (EVM). Verifying termination and arithmetic invariants for recursive dynamical systems over continuous domains is generally undecidable in the Blum-Shub-Smale model. Here, we present the formal verification and bare-metal empirical validation of WERR (Waves & Errors) and Phase III Orbital Error Dynamics (OED), a non-tensor decision paradigm that procedurally synthesizes non-linear decision boundaries on demand from a 24-byte coordinate seed $Θ= (c_x, c_y, \text{zoom})$ along the boundary of the Mandelbrot set ($\partial\mathcal{M}$). By projecting the recurrence $z_{n+1} = z_n^2 + c$ onto the modular residue ring $\mathbb{Z}/9\mathbb{Z}$ and the fixed-point domain $\mathbb{Q}_{16.16}$, we establish ten machine-verified theorems in Lean 4 (v4.34.1) with Mathlib4 and zero unproven conjectures (sorry): proving $\mathcal{I}_3 = \{0,3,6\} \subset \mathbb{Z}/9\mathbb{Z}$ ideal closure, universal fuel-bounded halting ($\le 9$ and $\le 12$ steps), absence of $\mathbb{Q}_{16.16}$ square overflow below $2^{63}-1$, non-constant boundary escape sensitivity, and a parametric EVM gas bound ($\le 22,557 \le 24,000$ gas). Evaluated on a 40-core Dual Intel Xeon server, the vectorized 36-iteration CPU kernel processes 100,000 decisions in 6.49 s (15,397 decisions/s, 0 Bytes VRAM, 15.15x speedup), while a sigmoidal outlier gate suppresses 100.00% of adversarial spikes while preserving 89.60% of clean baseline signals.
Blockchain transaction fees safeguarded against costless harm
Beyond Incentive Compatibility: Rational Harm-Proof Transaction Fee Mechanisms
Abstract: Transaction fee mechanisms (TFMs) allocate scarce block space in blockchains. Prior work focuses on incentive compatibility (IC): honest behavior maximizes the payoff of each strategic player. We introduce rational-harm proofness (RHP), which rules out deviations that harm honest participants without reducing the deviator's utility relative to honest behavior. IC alone does not exclude such costless harm: in a second-price auction, a losing bidder can raise the winner's payment without changing its own payoff. For finite block capacity k, we characterize TFMs satisfying RHP alongside user incentive compatibility (UIC) and miner incentive compatibility (MIC). In the plain model, where a single miner implements the auction, we prove a tight tetrilemma: no TFM simultaneously achieves positive miner revenue, UIC, MIC, and RHP against miner-user coalitions, while any three are jointly achievable. In the MPC-assisted model, where a committee of miners implements the auction using multi-party computation, we construct a randomized TFM with positive miner revenue satisfying UIC, MIC, and RHP against users, miners, and miner-user coalitions containing at most k users. Randomness is necessary to confirm transactions under congestion: any deterministic TFM satisfying UIC and user RHP in this model confirms no transactions when the number of submitted bids exceeds k. Finally, IC and RHP are incomparable for every strategic role in both models: mechanisms can satisfy either property without satisfying the other. These results extend transaction fee mechanism design beyond incentives to protection against costless harm.
Secure verifiable randomness improves blockchain lottery fairness
Verifiable Randomness for Blockchain-Based Lottery Systems
Abstract: As lotteries and other high-stakes decentralized applications increasingly depend on unpredictable randomness for their operations, the lack of a secure and transparent on-chain random number generator that is verifiable by all participants remains a critical open problem. Various approaches to blockchain-based random number generation have emerged over the years, each with their own strengths and limitations, and have consistently been superseded as blockchain technology evolved. This paper surveys existing approaches to on-chain randomness and proposes a new platform that builds upon the well-known commit-and-reveal scheme while directly addressing its principal vulnerability, the last revealer attack, in which the final participant can withhold their reveal in order to bias or abort the output upon seeing an unfavorable result. We further compare this solution with prior approaches and evaluate its entropy properties. The proposed architecture combines a web-based front-end with a Solidity smart contract deployed on the Polygon 2.0 blockchain. Implemented and tested on the Amoy testnet, the prototype is low-cost and simple to deploy, providing a practical, accessible proof-of-concept for verifiable on-chain randomness.
BFTide improves distributed system reliability by adaptive protocol switching
Adaptive Switching Between Leader-Based and Leaderless BFT Protocols
Abstract: Byzantine fault-tolerant (BFT) protocols are known for providing operational consistency and resilience in distributed systems. However, evolving network conditions, often driven by the network's inherent dynamism or adversarial influence, make it suboptimal to rely on a static protocol at all times. Existing BFT protocol adaptation solutions switch only among leader-based protocols and coordinate each switch through a separate consensus round, leaving them ineffective at handling severe asynchrony or situations in which an adaptive adversary targets the network's leader. We propose BFTide, a protocol adaptation architecture that enables a BFT system to intelligently and swiftly switch to a suitable protocol as network conditions shift. BFTide integrates a novel protocol switching layer that embeds protocol transition logic into the ongoing BFT operation, enabling safe and low-overhead transitions between partially synchronous leader-based protocols and asynchronous leaderless protocols. It further incorporates an offline-trained reinforcement learning policy that allows nodes to propose protocols at runtime based on observed system metrics. Experimental results show that BFTide reduces transaction latency under adverse network conditions compared with static BFT protocols and the state-of-the-art BFT protocol adaptation scheme BFTBrain (NSDI'25), while maintaining comparable throughput. The switching layer adds a modest 10-21% overhead to median latency when idle and requires no separate consensus round per switch.
Private mempool hiding needs strong lower bound to block sandwich attacks
How Much Must a Private Mempool Hide? Exact Leakage Thresholds for Sandwich Attacks
Abstract: Private and encrypted mempools hide pending transactions to stop sandwich attacks and other forms of maximal extractable value (MEV), but what they hide is rarely everything: a transaction's pair, direction, and a coarse range for its size can still leak. How much leakage makes sandwiching pay? We answer exactly for a fee-free constant-product automated market maker, the pricing rule behind Uniswap v2. Traders observe an interval containing the victim's size and bid in a first-price auction for the right to sandwich it, and the winning front-run must keep the victim's trade executable at every size in the interval. The answer turns on the smallest size consistent with the leak. It alone determines the feasible front-runs, the largest feasible front-run is optimal for pointwise, expected, and worst-case profit alike, and the guaranteed profit has a closed form. When execution is costly, a privacy layer that wants to rule out sandwiches profitable at every consistent size may therefore reveal anything about the size except a lower bound above an explicit threshold; the upper end of the range is irrelevant. With two or more symmetric traders, every pure-strategy perfect Bayesian equilibrium of the auction hands the entire expected net rent to the auctioneer. If the direction is hidden too, no non-contingent first leg front-runs both possible directions, while post-trade arbitrage can survive even perfect pre-trade hiding.
BenX hash function improves hardware use and speeds up proof verification
BenX: Resource-Sharing Permutations for Computational Integrity
Abstract: Cryptographic hash functions over integers modulo a prime play a decisive role in the efficiency and security of proof systems for computational integrity. Early designs focused on compact arithmetic circuits and efficient software execution, primarily targeting general-purpose CPUs rather than hardware accelerators. This work focuses on enabling efficient resource sharing and hardware acceleration alongside efficient software execution. We propose BenX, a permutation-based hash function designed for hardware acceleration, fast CPU execution, and low circuit complexity in proof systems. To construct the underlying permutation, we turn the Benes network into an invertible function over $\mathbb{F}_p^2$ using a Dickson polynomial. Its structure yields a permutation particularly suited to hardware resource sharing and acceleration. Fully pipelined on FPGA, BenX matches the throughput of Poseidon2, with 1.36x and 2.15x lower latency for Goldilocks and BabyBear, respectively. Although larger as a standalone core, it makes more effective use of shared hardware: in our dual-mode architecture, where the NTT and hash share field multipliers, BenX keeps 100% of them busy, compared with 6.25-20.3% for the partial rounds of Poseidon and Poseidon2. In software, BenX outperforms Poseidon in all tested 31- and 64-bit configurations, but is slower than Poseidon2, except for the 16-element BabyBear instance. In zero-knowledge proofs, BenX proves Goldilocks permutations 6-10x faster than Monolith. Its compact arithmetization uses about 36% fewer trace cells than Poseidon and Poseidon2 over BabyBear, while its fast variant requires 1.3-2.6x the prover time of Poseidon2.
Steelhead improves blockchain consensus for changing networks
Steelhead: Interleaving Partially Synchronous and Asynchronous Commit Rules on a Shared DAG
Abstract: Dual-mode consensus protocols are fast when the network is partially synchronous and remain live under asynchrony. We introduce Steelhead, a dual-mode mechanism that composes a partially synchronous and an asynchronous commit rule over one DAG: every k-th round is decided by the asynchronous rule, whose leader a common coin reveals after the votes, and all other rounds by the partially synchronous rule. Every interval, validators replay the committed DAG under each candidate period, adopt the one with the fewest expected message delays, and fall back to k = 1 when the output stalls; the asynchronous rule applied to the coin rounds alone keeps the protocol live. Steelhead sends no message beyond the DAG's blocks, not even to agree on the period, and opens a coin only on the rounds that need a hidden leader. It is generic over pairs of DAG commit rules that share a committee; we instantiate it with Mysticeti and Mahi-Mahi at n >= 3f+1 and with the two variants of BlueBottle at n >= 5f+1. We prove it safe and live, and provide mechanized proofs in Lean 4. In simulation, Steelhead matches the partially synchronous protocol in a healthy network, stays close to the asynchronous one when network conditions stall the partially synchronous one, and adapts quickly in both directions.
Ethereum voting prototype offers public audit for hospital ethics committees
A Lightweight Ethereum Voting Prototype for Hospital Ethics Committees with Receipt-Based Inclusion Verification
Abstract: This paper presents a Solidity, Hardhat, React, MetaMask, and ethers.js prototype for hospital ethics committee voting. Role controls, case-state checks, duplicate vote controls, and a receipt hash support public audit and transaction inclusion verification. Because vote events expose wallet addresses and vote values, the design provides pseudonymous auditability, not anonymous or secret-ballot voting; the receipt is neither receipt-free nor coercion-resistant. Evaluation reports 22 passing functional tests and local Hardhat gas use, including 284,137 gas per vote. A 12-participant simulation used assumed probabilities and is not human-subject evidence. Residual risks include multiple wallets, administrator or frontend compromise, credential reassignment, front-running, denial of service, and untested adversarial paths. Confidential deployment requires governed enrollment, encrypted ballots, independent audit, adversarial testing, reproducible benchmarks, and a real user study.
Zero knowledge proofs enable verifiable spectrum sharing with privacy
zkSAS: Practical Zero-Knowledge Proofs for Verifiable Spectrum Access Management
Abstract: Dynamic Spectrum Access (DSA) through the Spectrum Access Systems (SAS) elevates spectral efficiency, yet existing centralized models face allocation logic opaqueness and a lack of independent verifiability. While blockchain-based SAS architectures offer transparency and verifiability by default, they introduce critical privacy risks and prohibitive on-chain computational overhead. We introduce zkSAS, a practical zero-knowledge proof (ZKP) system designed to address the verifiability and privacy gaps in SAS deployments, with direct applicability to both the existing CBRS SAS model and blockchain-based SAS models. The system features a suite of ZKP circuits, encompassing proofs of allocation constraint validity and proofs of move list validity to verify that channel assignments and move list-based incumbent protection measures, respectively, adhere to regulatory constraints without exposing sensitive user data. Comprehensive evaluation of our prototype in both centralized and blockchain-based settings indicates that while proof generation scales with spectrum user population, verification remains lightweight and constant-time. We envision that zkSAS offers a scalable and practical path to secure, verifiable dynamic spectrum sharing.
Evage automates profitable blockchain trading strategies across chains
EVAGE: Autonomous MEV Generation and Adaptation via Multi-Agent Harness
Abstract: Maximal Extractable Value (MEV) has evolved into a major economic force in blockchain ecosystems, yet its capture is dominated by experienced teams, and both strategy design and implementation rely on manual expert work that scales poorly across heterogeneous protocols and chains. We present EVAGE, the first fully autonomous multi-agent framework for end-to-end MEV strategy generation and adaptation. Equipped with three specialized operation modes, it automatically discovers novel MEV variants, adapts execution logic across disparate protocols, and ports strategies between chains, including Layer-1 and Layer-2 networks. To avoid inference latency on the critical MEV execution path, EVAGE generates and refines MEV bot code offline rather than making real-time decisions directly. Under the coordination of an orchestrator agent, three specialized subagents collectively implement and repair the full MEV bot workflow via closed-loop diagnostics, eliminating human intervention while producing validated and deterministic Proof-of-Concept implementations. We evaluate EVAGE on over 1.5M blocks from each of Ethereum, Base, and BNB Smart Chain (BSC). On Ethereum, EVAGE uncovers five novel MEV strategy variants, yielding a profit increase of 1.02$\times$ to 15.97$\times$. It also successfully adapts 11 MEV strategies from CPMM to both CLMM and Balancer V2 and ports strategies from Ethereum to Base and BSC, all with less than 60 dollars in LLM token costs.
Renegade dark pool cryptography fails to ensure true privacy and fairness
Cryptographic Security Is Not Enough: Privacy Gaps in the Renegade Decentralized Dark Pool
Abstract: Dark pools are designed to provide pre-trade privacy, liveness, and post-trade confidentiality - concealing order flow before execution and limiting information leakage after. Decentralized dark pools, such as Renegade, aim to replicate these properties without custodial risk, using secure multi-party computation (MPC) and zero-knowledge proofs for private order matching and verifiable settlement. We show that Renegade's cryptographic guarantees do not deliver these dark pool properties in practice. MPC-with-abort ensures correctness but not fairness: a party may learn the match result and abort without penalty, breaking pre-trade privacy. We demonstrate that the protocol's discovery layer further leaks trading intent before MPC even begins, and that sustained probing via selective abort can probabilistically reconstruct counterparty order history, threatening post-trade confidentiality. We also show that the absence of input-consistency checks prior to MPC execution enables a griefing attack using invalid state commitments requiring no real token holdings that continuously locks honest users' wallets and wastes compute, breaking liveness under sustained conditions. We further analyze over 700,000 Renegade transactions on Base and probe the P2P layer, finding that the network is effectively centralized: 88% of traffic routes through a handful of relayers, with only four nodes sustaining the P2P layer. Since relayers hold their users' wallet state in plaintext, this concentration means the system operates as a centralized orderbook in practice - reproducing off-chain the information asymmetry that dark pools are designed to eliminate. Together, our results show that cryptographic privacy does not imply dark pool security: pre-trade privacy, liveness, and post-trade confidentiality each require additional protocol-level guarantees beyond MPC correctness.
Transformer model improves detection of Solidity smart contract bugs
Solidity Meets LLMs: A Transformer-Based Approach to Smart Contract Vulnerability Detection
Abstract: The growing adoption of blockchain technologies, particularly the Ethereum platform, has amplified the critical role of smart contracts in decentralized applications. However, the increasing complexity and financial value of these contracts make them prime targets for cyber attacks. In this work, we present a transformer-based approach for the detection of vulnerabilities in smart contract fragments written in Solidity. Leveraging the representational power of pre-trained Large Language Models (LLMs), we construct a robust pipeline that includes the definition of a ground truth dataset, labeling code fragments as vulnerable or safe. We then fine-tune a BERT-based architecture on this dataset, enabling the model to capture the syntactic and semantic patterns specific to Solidity code. Our fine-tuned model demonstrates strong performance, achieving an F1 score of 92%, and highlighting the effectiveness of LLM adaptation in enhancing smart contract security through deep contextual understanding.
Secure multiparty computation with verifiable real-world locations and times
I Prove, Therefore I Am: Spatiotemporal Multi-Party Computation
Abstract: Secure multiparty computation (MPC) enables mutually distrustful parties to compute on private digital inputs. We initiate the study of spatiotemporal MPC, extending this paradigm to functionalities whose inputs additionally depend on physical facts such as the parties' locations, times, or trajectories. Such protocols must simultaneously hide spatiotemporal information and ensure its physical consistency: a malicious party should not be able to make the functionality operate on a spatiotemporal input inconsistent with its actual physical state. The main conceptual challenge is to formulate extraction of spatiotemporal information within the simulation-based security framework. We introduce arguments of spatiotemporal knowledge, following the principle "I prove, therefore I am:" rather than defining physical presence directly through a mathematical relation, we define it operationally through the ability to complete a sound spatiotemporal verification protocol. Accordingly, an extractor recovers a spatiotemporal point from a successful prover and certifies its physical validity by using the extracted prover to succeed in an auxiliary spatiotemporal verification protocol. Building on this notion, we define universally composable (UC) security for spatiotemporal MPC, capturing privacy, physical consistency, and composability. We provide constructions achieving this new MPC notion. We first construct UC-secure commit-and-prove of spatiotemporal knowledge: in the CRS model under LWE against quantum provers without pre-shared entanglement, and in the QROM against quantum provers with unbounded pre-shared entanglement. Using these protocols, we obtain UC-secure spatiotemporal MPC from semi-honest post-quantum MPC. We also extend our framework to support quantum functionalities with classical spatiotemporal input.
FPGA accelerator speeds up secure proof computations for scalable blockchain
FASTAR: FRI Accelerator for Scalable Transparent ARguments of Knowledge
Abstract: Zero-Knowledge Proofs (ZKPs) enable a prover to cryptographically convince a verifier of the validity of a statement without revealing any underlying secrets, forming a foundational primitive for verifiable computation. The ZKP landscape is undergoing a fundamental shift from classic zk-SNARKs such as Groth16, which rely on trusted setup and are vulnerable to quantum adversaries, toward transparent, post-quantum constructions such as zk-STARK. These systems achieve post-quantum security by relying solely on collision-resistant hash functions, however, at the cost of substantial computational overhead. In particular, the Fast Reed--Solomon Interactive Oracle Proof of Proximity (FRI) protocol dominates prover complexity, generating massive data volumes, repeated Merkle-tree commitments, and irregular memory access patterns that limit performance and energy efficiency on general-purpose processors. To address these challenges, this work proposes FASTAR, a novel FPGA-based accelerator for the FRI protocol. Unlike accelerators that pursue fixed high-performance kernels on expensive ASIC process nodes, FASTAR adopts a constraint-driven design methodology. Our framework is implemented with High-Level Synthesis (HLS) and composed of fully parameterizable building blocks for the major stages of FRI, including polynomial evaluation, recursive split-and-fold, and Merkle-tree construction. From user-provided board specifications, FASTAR automatically generates hardware implementations tailored to the resource and memory constraints of the target FPGA, enabling deployment across a wide range of platforms without manual redesign.
Blockchain protocol stops front running by randomizing transaction sharing
Mitigating Front-Running Attacks through Fair and Resilient Transaction Dissemination
Abstract: In modern blockchains, efficient, fair, and faulttolerant information dissemination is critical for performance and security. Several stages of the transaction lifecycle are affected, from the creation and dissemination of transactions to the dissemination of blocks in the consensus layer. Mempool protocols, such as L{Ø}, already address some of modern blockchains' security threats. However, others remain unless fairness is embedded most fundamentally in the dissemination layer used by these protocols to share transactions and blocks and to reconcile mempools. This paper introduces HERMES, a novel dissemination protocol for mempools that leverages robust minimal structures to optimize data propagation, balance load, and ensure fairness despite faults and Byzantine actors. Specifically, we address front-running attacks by randomizing the choice of an overlay structure while forcing nodes to prove adherence to the mempools' dissemination policies and the random choice made. Experimental results show significant performance improvements compared to traditional broadcast protocols for both permissioned and permissionless blockchains.
Post quantum signatures need blockchain specific features for secure use
Domain Specific Post Quantum Signatures for Blockchains
Abstract: Blockchains need more than post quantum single signer signatures. They need consensus profiled authentication objects with canonical bytes, priced invalid input rejection, stable transaction identifiers, hybrid downgrade resistance, public aggregation, merge semantics, accountable signer evidence, forward secure committee rotation, and light client consequences. We argue for domain specific post quantum signatures for blockchain roles, analogously to how hash function engineering produced domain specific primitives for hash table DoS and arithmetized proof systems. We formalize transaction authorization and quorum certificate requirements, instantiate them on Bitcoin, Ethereum, and a Sei Giga style high throughput BFT stress profile, and evaluate ML-DSA, SLH-DSA, Falcon/FN-DSA, HAWK, MAYO, SNOVA, UOV/QR-UOV, FAEST, SQIsign, LaBRADOR Falcon, Squirrel, Chipmunk, and DKKW/LeanSig. The conclusion is blunt. NIST single signer signatures are necessary components, although none of the current schemes is a drop in replacement for the signature layer of modern public blockchains. The missing object is a consensus ready post quantum signature profile, not another generic size table.
New method reduces signing key size in prefix puncturable signatures
Prefix Puncturable Signatures with Smaller Signing Key from HIBS
Abstract: Puncturable signatures, proposed by Bellare et al. (EUROCRYPT 2016), allow a signing key to be punctured (updated) so that it loses the ability to sign particular messages while retaining the ability to sign all others. Halevi et al. (ASIACRYPT 2017) introduced prefix puncturable signatures, in which the signing key can be punctured with respect to a target prefix so that it cannot sign messages whose prefixes match the target prefix. So far, several generic constructions of prefix puncturable signature schemes have been proposed, including constructions based on identity-based signatures (IBS) (ESORICS 2022) and delegated constrained signatures (IEEE Trans. Inf. Forensics Secure. 2024). However, these constructions suffer from drawbacks in terms of key size. When the prefix space is the set of all l-bit strings, the former construction requires a signing key consisting of 2^{l} IBS signing keys. The latter construction, when instantiated with a lattice-based delegated constrained signature scheme, yields a punctured signing key whose size grows quadratically with the number of puncturing operations Q^{Punc}. In this paper, we present a generic construction of prefix puncturable signatures from hierarchical identity-based signature (HIBS) schemes. When the prefix space is {0,1}^{l} and our construction is instantiated with the lattice-based HIBS scheme HIBS^{GPV} by Ruckert (PQC 2010), our construction achieves a punctured signing key size bounded by O(lQ^{Punc}).
Ethereum defi benchmark reveals challenges in protocol and contract shifts
ETH-TraceBench: A Large-Scale Event-Stream Benchmark for Ethereum DeFi under Temporal, Protocol, and Contract Shift
Abstract: Ethereum decentralized finance (DeFi) provides a public, time-stamped record of transaction-level event streams, but the same public symbols can create strong machine-learning shortcuts. We introduce ETH-TraceBench, a benchmark for evaluating Ethereum DeFi representations under temporal, protocol, pool/infrastructure, and symbolic shift. The raw event universe covers January 2021-December 2025 and contains 1.35 billion transactions with logs and 5.01 billion raw log rows. Model evaluation uses a fixed 911,267-instance supervised sample, training on 2021-2024, selecting models on 2025H1, and testing on 2025H2. Simple models perform strongly on the aggregate temporal test: TraceStats-GB reaches 0.953 macro-F1 and TopicEmitterHashMLP 0.959 on the canonical DEX test set. Performance drops sharply under protocol novelty, with macro-F1 of 0.794, 0.743, and 0.766 for TraceStats-GB, TopicEmitterTrace-SGD, and TopicEmitterHashMLP, while strict unseen-pool scores remain 0.927, 0.897, and 0.935. Uniswap v4 and Ekubo v1, both absent from supervised training, are materially harder than the full test. Jointly masking emitter and topic identity reduces DEX macro-F1 to 0.916 and liquidation macro-F1 to 0.774 for TopicEmitterTrace-SGD. A standard Transformer over log-index-ordered events provides no consistent advantage over a deterministic shuffle of the same events, indicating that high aggregate scores can arise without sophisticated chronological modeling. A natural-prevalence audit estimates 2025H2 DEX prevalence among logged Ethereum transactions at about 22.5%, and a deterministic 400-transaction audit finds complete agreement with task label sources and independently re-queried raw-log counts. ETH-TraceBench therefore treats difficult transfer and controlled-input conditions, rather than a single aggregate score, as the main evaluation target.
Trusted execution environments enable secure data sharing with digital rights tokens
Verifiable Computation with Trusted Execution Environments and On-Chain Digital Rights Tokens
Abstract: We present an architecture that enables data owners to combine private data into data pools using Trusted Execution Environments (TEEs) and manage these pools by issuing narrowly scoped computational rights, encoded as Digital Rights Tokens (DRTs), to third-party data analysts. Each DRT binds specific open-source code to a pool and is issued and redeemed on a distributed ledger. Data analysts can obtain the right to execute open-source code on the combined sealed data inside a TEE and receive the result from this code execution, but not the underlying data. We argue for a control-centric view of privacy in which creators retain ex ante control over how their data is processed. A reference implementation runs WebAssembly (WASM)/Python jobs over sealed datasets and records redemptions on Solana, illustrating the feasibility and limitations of the platform.
Efficient blockchain consensus protocol cuts computation and delays
PoVD: Efficient Consensus Protocol based on Verifiable Delay Function
Abstract: Consensus protocols ensure the robustness and scalability of blockchains and decentralized applications built on them. However, existing consensus mechanisms often impose high computational cost or require heavy communication overhead. To address these challenges, we propose proof of verifiable delay (PoVD), a lightweight consensus protocol based on the verifiable delay function (VDF). We present the detailed protocol of PoVD, including the block mining and verification rules, and illustrate how PoVD can flexibly adjust the block time distribution according to the network condition. Through mathematical proof, we point out that, under a relatively weak network assumption, PoVD can achieve a lower fork rate than PoW while maintaining the same throughput. Our experiments verify that PoVD exhibits low computation and communication complexity and can also improve the blockchain consistency, making it particularly suitable for resource-constrained nodes and bandwidth-limited networks.
XIR framework greatly expands blockchain message reachability
XIR: A Framework for Interoperability across Cross-Chain Protocols Based on a Verifiable Intermediate Representation
Abstract: Cross-chain protocols enable applications to exchange messages across blockchains. Under point-to-point configurations, communication depends on a direct connection between the source and destination blockchains, limiting blockchain reachability and requiring additional configurations to connect more blockchains. To quantify this problem, this paper analyzes approximately 25 million mainnet cross-chain transaction events collected from six protocols (Axelar, CCIP, Hyperlane, LayerZero, Relay, and Wormhole) between January and October 2025. The resulting graph covers 286 active blockchains and 11,935 directly connected ordered blockchain pairs. These connections provide a direct reachability of 14.64%, while full direct connectivity would require 81,510 point-to-point configurations. We present XIR, a framework for interoperability across cross-chain protocols based on a verifiable intermediate representation. This representation binds an application message to an ordered record of authenticated cross-chain protocol deliveries, preserving message identity and verification history across protocol boundaries. XIR Gateways and XIR Adapters use this representation to compose existing connections into same-protocol and cross-protocol multi-hop paths. We implement an XIR prototype integrating Hyperlane and LayerZero and evaluate it in local and public-testnet environments. Theoretical analysis and evaluation show that, with correctly configured cross-chain protocol connections, XIR avoids 67,018 additional point-to-point configurations, equivalent to 84.88% of the total required by a point-to-point configuration baseline serving the same reachable pairs, and increases reachability from 14.64% to 96.86% of all ordered blockchain pairs.
Framework improves hardware speed and size for elliptic curve operations
Locus: A Framework for Exploring and Optimizing Point Addition Hardware for Zero-Knowledge Proofs
Abstract: Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving and verifiable computation, but their cryptographic primitives impose high computational overheads. One such primitive is point addition (PADD) on elliptic curves. Several prior works have implemented PADDs in hardware, but only for a few specific elliptic curves and design points, leaving a large design space unexplored, and lacking systematic guidance on hardware design trade-offs. To address this gap, we present Locus, a framework dedicated to optimizing and exploring point addition hardware. Given the parameters of any elliptic curve in a supported equation form, Locus automatically generates ASIC and FPGA implementations of PADD, enabling systematic exploration of the PADD design space. Using Locus, we conduct the first comprehensive hardware-focused study of PADD designs, exploring trade-offs over 1,000 design points. On a 12nm technology node, our framework produces PADD designs that yield a $2.71\times$ geomean speedup and $3.11\times$ geomean area reduction compared to prior ASICs, $34.67\times$ geomean speedup over CPU, and $3.15\times$ geomean speedup on end-to-end proof generation when integrated into a prior ZKP accelerator at iso-area. Locus is available at https://github.com/cryptolets/cryptolets/tree/locus.
Selective silence attacks disrupt blockchain consensus and how to detect them
Vigil: Accountable Liveness against Selective Silence
Abstract: BFT accountability is well understood for safety violations, and recent work attributes global liveness violations; \emph{recipient-selective} silence remains unresolved. A selectively silent adversary withholds messages from some honest nodes while behaving correctly toward others. It can stall consensus yet evade every existing mechanism. We initiate a systematic study of accountability against selective silence. Negatively, a lone attacker silent toward at most $f$ honest nodes is indistinguishable from an honest node, yielding a universal lower bound $K_{\mathrm{SI}} \ge f{+}1$ on the \emph{silence identification threshold}; moreover, any feedback-free repair after a silence-induced violation costs $Θ(n^3)$. Positively, \textsc{Vigil}, a Tendermint variant, matches these bounds with attack-adaptive forwarding, via bitmap cross-attestation, core-based membership, and challenge--response auditing. It pays $O(n)$ authenticators per node when no selective silence occurs (plus $Θ(n^2)$ bitmap metadata bits per node), relays in proportion to the attack's width (sub-threshold silence can force up to $n^3/27$ relays per view, a cost we price exactly), and majority-accuses any node silent toward more than a tunable resilience $τ_A$ of honest peers ($K_{\mathrm{SI}} = τ_A{+}1$, optimal at $τ_A = f$). We also price the residual sub-threshold griefing surface exactly and extend identification to $x$-partial synchrony. Real-network experiments on a three-region WAN, together with a simulator held to exact equality with every closed form, confirm each threshold and cost: at $2\%$ loss, an $f{+}1$ accusation bar falsely accuses $91.2\%$ of honest nodes, while our majority bar accuses $0.002\%$.
Blockchain prediction markets vulnerable to trade failures and attacks
Ghost-Filled Orders: Detecting and Testing Atomicity Violations in Non-Custodial Prediction Markets
Abstract: Blockchain based prediction markets combine offchain order management with onchain settlement. This architecture supports user controlled custody, since users keep funds in wallets or smart contracts while submitting signed orders to an offchain order book. However, it creates an atomicity gap. An order may be valid when accepted or matched offchain, but become invalid before the corresponding onchain settlement transaction is executed. This behavior, often called ghost filled orders by the community, can cause trades that appear filled offchain to fail onchain. This paper studies this atomicity gap through a case study of Polymarket. We show how the delay between offchain order acceptance and onchain settlement allows adversaries to invalidate unfavorable orders after observing market outcomes or price movements. We then quantify the scale and financial impact of this behavior over a nine-month period from August 12, 2025, to May 22, 2026, using 1.8 million reverted transactions involving Polymarket official smart contracts. Our analysis separates attacker profit from market and user loss, and develops conservative measurement rules to avoid overclaiming impact. We further develop a methodology for testing other blockchain based prediction markets and apply it to three additional markets. We find that all three are vulnerable to the same class of attack, and that one design enables direct attacker profit. We have reported the findings to all three projects; one project had acknowledged the issue at the time of the study.
Byzantine reliable broadcast achieves causal ordering among messages
Byzantine Reliable Broadcast with Causal Ordering
Abstract: Reliable and total-order broadcasts in the Byzantine-fault model are well studied, but adding causal order has received comparatively little attention, largely due to the complexity that stems from actions of Byzantine processes. Existing solutions almost exclusively build causal ordering on top of total-order broadcast. The combination of causal order with reliable broadcast remains rare, and the few solutions that exist adopt the classical definition of causality based on events occurring at individual processes (the happened-before relation). This definition is not sufficient to enforce causal ordering among broadcast messages: Byzantine processes can lie about, omit, and forge dependency information and thereby violate the causal order among self-reported events. Such manipulations remain indistinguishable from correct behavior to any single observer. We demonstrate the issue and its consequences via a front-running attack. To close this gap, we extend the notion of reliable broadcast to externalize local potential knowledge. We use this to formalize the first complete definition of causal message ordering in reliable broadcast under Byzantine faults. Unlike the classical formalization, this notion is grounded in the joint observations of a sufficiently large group of correct processes rather than a process's own view. Building on this definition, we characterize the properties of a Byzantine reliable broadcast channel that guarantees causal ordering. We then present an efficient protocol that satisfies these properties: it is resilient to the optimal number of $f < n/3$ Byzantine faults and for one instance that broadcasts payload message~$m$, it has bit complexity $O(n^2(|m| + λ+ n))$, where $λ$ denotes the maximal size of a unique (cryptographic) label for~$m$. Finally, we prove the protocol achieves Byzantine reliable broadcast with causal ordering.
TasmScan improves smart contract analysis for TON virtual machine
TasmScan: Continuation-Aware Taint Analysis for TVM Bytecode with Savelist Abstraction
Abstract: The Open Network (TON), with a peak market capitalization exceeding $20 billion and over 175 million activated on-chain addresses, relies on the TVM (TON Virtual Machine) to execute smart contracts. TVM uses first-class continuations with savelists to manage control flow and register state across continuation invocations. Since savelist-captured registers allow data to flow across continuation boundaries without passing through the operand stack, bytecode-level analyses cannot construct complete data flow tracking without explicitly modeling savelist semantics. We present TasmScan, the first bytecode-level static analysis framework for TVM that enables cross-continuation data flow reasoning without requiring source code. TasmScan models savelist semantics via forward register analysis with a formal over-approximation guarantee for exact-resolved save sites and locally tracked register definitions, then lifts bytecode into TASIR, a typed intermediate representation, and performs path-sensitive taint analysis with context-aware sources to detect defects. We evaluate TasmScan on 2,921 contracts from the TON verifier registry and a labeled benchmark of 208 contracts with human-confirmed ground truth. On the full corpus, TasmScan resolves 294,546 dynamic continuation targets with 100% precision; ablation confirms that savelist propagation is essential for resolving indirect register calls that depend on cross-continuation register passing. On the benchmark, TasmScan detects 95.3% of defects across five classes with 96.8% precision. A 366-pair stratified sample from the full corpus estimates 85.8% overall precision. TasmScan offers a 17x median speedup over the state-of-the-art symbolic-execution baseline, and in the path-analysis comparison completes 100% of analyses with zero crashes or timeouts.
ZkVM verification made faster and more reliable with ZEBRA
Efficient Branch-and-Bound Testing and Verification of zkVMs
Abstract: Zero-knowledge virtual machines (zkVMs) enable verifiable execution of general-purpose programs by translating virtual machine semantics into algebraic constraints over execution traces. The correctness of these constraints is critical: a single incorrect constraint can admit forged proofs (under-constrained) or reject valid executions (over-constrained). Existing approaches do not provide meaningful guarantees at production scale: fuzzers and unit tests often miss bugs, SMT solvers struggle with the size and nonlinearity of constraints, and theorem provers require substantial manual effort. We present ZEBRA, a fully automated verification and bug-detection framework: for a given program and input, the constraint must admit exactly one valid execution trace - no more and no fewer. This reduces zkVM verification to a solution-set cardinality problem over a canonical trace space, where redundancies such as null-row padding and non-deterministic permutations are eliminated prior to counting. To compute cardinality tractably, ZEBRA lifts analysis from finite-field witnesses to an integer interval lattice, exploiting a structural sparsity property of zkVM constraints: across 5 real-world zkVMs, constraints utilize only 14.0% of their theoretical connectivity capacity on average. This sparsity enables tight interval propagation with limited approximation error. ZEBRA performs a parallel branch-and-bound search that either produces a concrete counter-example or certifies the absence of violations within a bounded region. We evaluate ZEBRA on five real-world zkVMs. ZEBRA discovers 11 zero-day bugs; 6 have already been independently confirmed and 3 have been fixed by developers. Compared to SMT-based verification, ZEBRA is 51.5x faster, verifies 16.5 percentage point more instances, and its range verification provides up to 63x efficiency gain over repeated single-input verification.
Smart contract fuzzing improves with large language models
EchoFuzz: Empowering Smart Contract Fuzzing with Large Language Models
Abstract: Smart contracts, serving as the cornerstone of decentralized applications, autonomously manage trillion-dollar digital assets, making them attractive targets for attacks. Fuzzing has emerged as a promising technique for detecting vulnerabilities in smart contracts, yet existing methods face two main challenges. (1) The logical gap in state transitions and combinatorial redundancy hinders effective tradeoffs between bug detection efficiency and state space exploration cost, leading to critical execution paths to be overlooked. (2) Rule-based sequence mutation strategies suffer from path redundancy and inadequate guidance from contract logic, resulting in performance bottlenecks that stall the exploration of in-depth vulnerability-oriented paths. To tackle these challenges, we propose EchoFuzz, an LLM-guided fuzzing framework introducing Vulnerable Function Call Sequences (VFCS) - minimal, behavior-preserving execution paths that expose bugs through key state transitions. EchoFuzz consists of two key procedures. First, we develop a chain-guided LLM approach, that combines static analysis with logical understanding to generate contract-specific VFCS candidates that eliminate combinatorial redundancy. Second, we adopt an iterative fuzzing strategy that uses LLMs with real-time feedback to adaptively steer fuzzer toward uncovered branches. Experiments show EchoFuzz outperforms state-of-the-art methods, achieving 29\% higher branch coverage and detecting 62\% more vulnerabilities. It also found 37 previously unknown vulnerabilities in real contracts, showing strong practicality.
Post-quantum cryptography protects bitcoin lightning network communications
PQLN: Post-Quantum Security for the Bitcoin Lightning Network's Off-Chain Surfaces
Abstract: A cryptographically relevant quantum computer will break the elliptic-curve cryptography behind Bitcoin and its Lightning Network, the most widely used payment channel network. Even a post-quantum consensus upgrade of Bitcoin would not cover Lightning's off-chain surfaces, so its gossip, peer transport, invoices, payment onions, and offers need separate protection. An adversary can already record Lightning's encrypted traffic today and decrypt it once such a computer exists. Lightning can therefore move to post-quantum cryptography now, without waiting for Bitcoin, and stop such harvest-now-decrypt-later attacks along with node impersonation, invoice forgery, and payment deanonymization. In this paper, we propose PQLN, a hybrid post-quantum extension of Lightning that protects all of these surfaces with the lattice-based standards ML-DSA and ML-KEM. PQLN distributes post-quantum node identities through Lightning's gossip, hybridizes the transport handshake, adds post-quantum signatures to invoices, commits post-quantum keys in offers, and makes payment onions hybrid. Since post-quantum material is much larger than its elliptic-curve counterpart, we introduce techniques that fit it into Lightning's existing message formats and size limits. We analyze the security of PQLN against a quantum adversary and implement it in rust-lightning, a major Lightning implementation. Our evaluation with real Lightning nodes shows that PQLN nodes interoperate with unmodified nodes. The added cryptographic operations take at most 0.33 milliseconds, and the main cost is communication, since gossip data grows about tenfold with ML-DSA and about fourfold with the smaller Falcon. To our knowledge, PQLN is the first post-quantum design, implementation, and evaluation for Lightning.
IntentFuzz finds vulnerabilities in cross-chain blockchain bridges
IntentFuzz: A Protocol-Aware Fuzzer for Automated Invariant Violation Detection in Intent-Based Cross-Chain Bridges
Abstract: Cross-chain bridges move value between blockchains. Intent-based bridges are a variant where a solver fulfills a user's declared outcome and an off-chain settlement layer later reconciles the fill against the deposit. Existing smart-contract fuzzers and static analyzers only flag known-bad code patterns or require protocol-specific hand-written assertions. This work formalizes a taxonomy separating invariant violations, safety properties a contract must enforce locally, from settlement exposures legitimately delegated to the off-chain settlement layer, and proposes IntentFuzz: a protocol-aware fuzzer that recovers a bridge's intent structure and deposit/fill function roles directly from unannotated Solidity source, then synthesizes multi-step fuzz sequences using an LLM-based fallback to help build call arguments. IntentFuzz recovers the correct intent structure in 9/9 benchmark protocols and classifies deposit and fill functions with 100% recall and 82% combined precision; across a corpus of 77 manually labeled contracts, it reaches 79.5% bridge-classification precision and 97.2% recall, and among confirmed bridges, struct selection reaches 88.6% precision and recall while deposit and fill classification each reach 100% recall. On 23 planted-bug mutants, IntentFuzz attains 100% recall and 100% precision, executing 273 templates (507 transactions in a median of 14ms per template). Across 24 real-world deployments, it confirms 17 genuine invariant violations under heuristic-only input generation, rising to 22 with its LLM-assisted tier enabled, spanning eight vulnerable GitHub repositories, each finding reproducible against public, deployed bytecode.
Verifiable delay proofs linked to fresh public challenges limit fast cheating
Fresh-Challenge VDF Attestations for Model-Relative Response Latency
Abstract: Can a finite verifier obtain public, model-relative evidence about response latency for sequential computation? Verifiable delay functions (VDFs) make this possible in principle: evaluation requires T sequential steps, whereas verification is efficient in the security parameter and polylogarithmic in the numerical value of T for standard constructions. Thus a delay can be astronomically large to evaluate yet succinctly represented and feasibly checked. A VDF proof for a chosen message alone is insufficient because it may be precomputed. We specify and analyze Fresh-Challenge VDF Attestations (FCLA), a protocol composition that binds a VDF to an unpredictable public challenge, a message, and independently auditable release and receipt records. Under explicit assumptions about VDF sequentiality, the challenge source, witness logs, and a calibrated upper bound on an adversary's sequential evaluation rate, an accepted FCLA transcript is inconsistent with post-challenge generation by an adversary in that bounded model. The result neither identifies a named claimant nor excludes relaying, outsourcing, or a faster unmodeled machine. A benchmark of the public reference implementation confirms the expected empirical separation between evaluation and verification on one documented machine. Our contribution is a protocol/design analysis and benchmarked reference implementation layer, not a new VDF construction or cryptographic primitive.
PoW blockchain denial-of-service attack becomes self-sustaining and profitable
PDoS: A Profitable Denial-of-Service Attack against Proof-of-Work Blockchain Liveness
Abstract: The security and liveness of Proof-of-Work (PoW) blockchains fundamentally depend on the economic rationality of miners. Existing incentive-driven denial-of-service attacks, such as BDoS, can deter rational miners from participating, but require the attacker to continuously absorb substantial economic losses and are therefore difficult to sustain in high-value networks. Meanwhile, prior infiltration-based withholding attacks are designed to extract revenue rather than to directly disrupt chain liveness. We present PDoS, a hybrid attack that combines block header signal deterrence with parasitic revenue extraction. PDoS disrupts blockchain liveness while exploiting the victim pool's share-reward mechanism to subsidize the attack cost, thereby lowering the adversarial hash-power threshold required to induce rational miners to shut down. We further show a counterintuitive result: in high-fee or high-MEV environments, higher block value can make PoW systems less secure by increasing the attacker's parasitic revenue and pushing the attack across the break-even point into a self-sustaining, or even profitable, regime. To the best of our knowledge, PDoS is the first attack to demonstrate that disrupting PoW blockchain liveness can be economically self-sustaining and even profitable.
Conditional transaction mechanisms optimize evaluation order for offline users
Opening the Strategic Pandora Box: Conditional Transaction Mechanisms
Abstract: Conditional transaction engines (CTEs) execute conditional instructions for offline users. This paper formalizes the mechanism-design problem within each engine invocation. A conditional transaction mechanism (CTM) decides which pending conditions to evaluate first because each evaluation delays the eventual write. We model this problem as Strategic Pandora, a discounted variant of the Pandora's box model with independent Bernoulli boxes. Agents report privately assessed success probabilities and, in the full model, values for the write action. We propose the reported-Weitzman mechanism (RW) and the reported-values second-price mechanism (RWSP). To compare revenue without a common prior, we introduce dynamic No-Betting Revenue. Under the stated competition and equilibrium conditions, every qualifying pure equilibrium of RW or RWSP earns a constant fraction of its corresponding dynamic NBR benchmark.
NEAR protocol sharding performance tested on everyday computer hardware
Shards on a Shoestring: Empirical Characterization of NEAR Protocol Nightshade Sharding on Commodity Hardware
Abstract: NEAR Protocol's Nightshade architecture targets one million transactions per second (TPS) through horizontal sharding of both state and computation. Published benchmarks were produced on expensive Google Cloud Platform infrastructure costing approximately \$700 per hour, leaving a significant reproducibility gap for academic research. We present the first independent empirical characterization of NEAR Nightshade sharding on commodity hardware: a Chameleon Cloud bare-metal node with 48 hyperthreaded Intel Xeon cores, 128\,GB RAM, and HDD storage at 80--100\,MB/s. We systematically sweep shard count from $N{=}1$ to $N{=}24$, measuring aggregate TPS, per-shard TPS, block time, BFT finality, memory, and disk I/O. We identify three distinct bottleneck regimes: L3 cache pressure at low $N$, witness gossip pipeline saturation at mid $N$, and coherence collapse at high $N$. A key unexpected finding is that HDD write latency acts as implicit flow control for the witness gossip pipeline. Removing it via RAM-backed tmpfs causes complete chain stall at $N{=}16$, with a 29$\times$ spike in orphan witness rate at 47\% CPU utilization. Aggregate TPS peaks at $N{=}8$ (+40\% over $N{=}1$) then reverses, with per-shard TPS collapsing 23$\times$ by $N{=}24$. Our dataset provides the first commodity-hardware calibration baseline for the companion SimPy sharding simulator.
Smart contracts need user conditions to resist frontrunning attacks
On Identifying Sound Conditions for Frontrunning Resistance
Abstract: Blockchains enable decentralized applications through smart contracts---interactive programs executed through consensus. However, the inherently asynchronous nature of blockchain transaction ordering introduces a class of vulnerabilities known as frontrunning attacks, which have caused millions of dollars in losses in major blockchains, such as Ethereum. Frontrunning attacks arise because users interact with smart contracts through transactions, which are added to the blockchain by designated nodes called miners. Miners can exploit their ability to reorder, delay, or insert transactions to gain an advantage over honest users, effectively frontrunning them. Yet, to date, the field lacks a rigorous definition of what it even means for a contract to resist such attacks. Worse, we show that existing dynamic detection approaches are fundamentally inadequate: in a large-scale study comprising 287 smart contract audits, 55% of the 393 reported vulnerabilities identified by leading smart contract auditors fall outside the scope of state-of-the-art detection criteria. To address this gap, we propose the first formal definition of frontrunning vulnerability for smart contracts. Our definition captures a key insight: resistance to frontrunning is not an intrinsic property of a contract alone, but depends critically on how honest users interact with it. Grounded in this observation, we develop a sound algorithm for synthesizing secure interaction conditions, alongside a prototype implementation that we apply to audited real-world contracts---revealing previously undiscovered vulnerabilities in two Ethereum contracts.
DeFiFlowBench benchmarks safety of natural language DeFi workflows
DeFiFlowBench: Benchmarking and Improving Safe Executability in Natural-Language DeFi Workflow Synthesis
Abstract: A structurally valid DeFi workflow can still authorize a costly trade. We introduce DeFiFlowBench, a benchmark of 207 team-authored prompts for natural-language DeFi workflow synthesis. It measures graph coverage, configuration completeness, and declared safety predicates, then tests supported trade configurations on a local EVM. Direct, constrained, and few-shot prompting produce 14-19 unsafe held-out executions per configuration under a fixed 5% price-impact cap. A slippage bound derived from a quote does not prevent the price impact of the order itself. We propose Koan-Safe, which combines a prompt-only intent parser, a replaceable generator, and structural repair with default safety parameters. On 75 held-out workflow prompts, its hybrid variant scores 0.67 on the static safety proxy, compared with 0.33 for the best baseline. Koan-Safe records no unsafe executions on the saved benchmark outputs. A matched-candidate ablation produces 14-17 unsafe executions when enforcement is disabled. Additional tests expose the limits of default injection: permissive existing thresholds can still authorize unsafe trades. A separately evaluated policy cap addresses this failure on a 36-case diagnostic grid. These results support explicit trade protections and execution-based evaluation, while distinguishing declared safety from a general guarantee.
Sound removal of extra checks speeds zero knowledge neural proofs
Sound Debloating of Redundant Checks in Zero-Knowledge Machine-Learning Circuits
Abstract: Zero-knowledge (ZK) proof systems for neural-network inference compile the model into a system of arithmetic constraints. Many of these constraints are redundant checks: range proofs, sign lookups, and bit decompositions who are globally entailed by the rest of the circuit through chains of reasoning that span distant gadgets. Removing them shrinks the circuit and accelerates proving, but the removal must be carefully justified: an unsoundly debloated circuit becomes forgeable, accepting witnesses the original would have rejected and so allowing a prover to claim, for example, that a neural network produced an output it never actually computed. Such soundness vulnerabilities are not hypothetical: under-constrained circuits in deployed ZK systems have enabled attackers to forge transactions and bypass verification entirely. We present an automated framework that removes redundant checks while provably preserving soundness. For each candidate removal, our tool first checks whether the rest of the circuit, on its own, can still rule out every value the removed check was excluding. Using whole-circuit abstract interpretation, the analysis searches for such alternative justifications and records them in a provenance graph; a check is then removed only when an alternative path through the graph still derives the facts that it is checking. This ensures that the debloated circuit opens no new forging strategy to an adversary. We evaluate circuits spanning MLP, CNN, RNN, and transformer architectures generated by two production frameworks (ezkl and zkml), with up to 25.3 million constraints. Our tool removes up to 48.7\% of constraints and reduces prover time by up to 72.8\%, without weakening security.
Byzantine agreements tolerate reordered messages with new security limits
Scalable Composition of Byzantine Agreements under Reorder Attacks
Abstract: Byzantine agreement (BA) is a foundational building block in distributed systems, and the security analysis of BA protocols under multi-instance executions has attracted increasing attention. However, most existing adversary models focus solely on party corruption and neglect important threats posed by adversarial manipulations of communication channels in the network. Through channel attacks, messages can be reordered across multiple executions and lead to violations of the protocol's security guarantees, In this work, we present the first adversary model that combines party corruption and channel attacks. Based on this model, we establish new security thresholds for Byzantine agreement under parallel and concurrent compositions, supported by complementary impossibility and possibility results that match each other to form a tight bound. For the impossibility result, we show that even authenticated Byzantine agreement protocols cannot be secure under parallel composition when $n \leq 3t$ or $n \leq 2c + 2t + 1$, where $t$ and $c$ denote the number of corrupted parties and communication channels, respectively, and $n$ is the number of parties. For the possibility result, we prove the existence of secure protocols for unauthenticated Byzantine agreement under parallel and concurrent composition, when $n > \max\{3t, 2c+2t+1\}$. We first provide general black-box compilers that transform any single-instance secure BA protocol into one that is secure under parallel and concurrent executions without additional security assumptions. To optimize performance, we further design refined compilers using erasure-correcting codes. These refined versions significantly reduce communication overhead, particularly for long messages, where they achieve a constant multiplicative overhead compared with the original protocol, thus achieving the same asymptotic communication complexity.
Guppy speeds up blockchain light clients with zero-knowledge proofs
Guppy: Efficient Light Clients via Recursive Zero-Knowledge Proofs
Abstract: Traditional light clients rely on validators committing to the entire blockchain state at every block via a state commitment such as a Merkle tree, allowing clients to verify facts using short proofs. However, maintaining large and ever-growing state trees imposes a significant burden on validators and lies on the critical path of block production. As a result, many modern high-throughput chains avoid this approach altogether. This work asks whether efficient inclusion proofs can be supported without requiring validators to maintain full state commitments. We present Guppy, a protocol that achieves this by having validators commit to just the state updates. An off-chain, untrusted service, secured by recursive Zero-Knowledge Proofs (ZKPs), then maintains a verifiable Merkle tree over the full state. This design keeps validator overhead negligible and does not increase the asymptotic complexity of block construction. Our design rests on two key technical ideas. First, a hash-chain commitment moves validator signature verification out of the ZK circuit, keeping the proving circuit efficient. Second, we design a parallel recursive proving pipeline that leverages cheap recursion in modern ZKPs to ensure latency grows only logarithmically with throughput. Our Plonky2-based implementation demonstrates that Guppy can maintain a Merkle tree of size 2^30 while processing thousands of updates per second, adding only 2-4 s of latency.
EventSpec finds event syncing problems in blockchain smart contracts
EventSpec: Defining and Detecting Event-Semantic Issues in Blockchain Ecosystems
Abstract: In recent years, smart contracts have become the backbone of decentralized applications (DApps), and off-chain systems such as bridges, wallets, and indexers rely heavily on event logs to track contract execution and state changes. However, the Ethereum Virtual Machine (EVM) does not validate or enforce event semantics, so logs can diverge from on-chain state, misleading off-chain systems into accepting incorrect state transitions. Existing smart contract vulnerability detection tools focus on logic bugs, with limited support for detecting event-semantic defects. To address this gap, we collect audit reports and incident cases and apply open card sorting to define five classes of event-semantic defects: event collision, state-event mismatch, unauthorized event emission, event emission mismatch, and event parameter mismatch. We propose EventSpec, which infers event specifications from a contract corpus via behavior inference and semantic-constraint extraction and applies differential checking to identify event-semantic defects in target contracts. We run EventSpec on 6,617 real-world contracts and evaluate detection effectiveness based on manually labeled results; EventSpec achieves an overall comprehensive precision of 90.17%. We further provide an off-chain evaluation harness that reproduces two off-chain attack vectors on any EVM-compatible chain: event origin confusion caused by unintended emitters and event-state desynchronization where events lack matching state updates. Using this harness, we demonstrate the feasibility of these attacks on bridge relayers, blockchain explorers, and NFT marketplaces, and report six wallet issues, four of which were confirmed (including a $600 bounty), with two remaining pending.
Market behavior reveals complex communication beyond single transactions
Your Agent Says Yes: Interpreting Adversarial Market Behavior Beyond Individual Transactions
Abstract: Transaction-local controls answer whether one financial request may proceed, but market behavior can be distributed across messages, agents, assets, and time. We study this interpretation gap in a virtual exchange populated by ten role-conditioned language-model agents. The agents communicate, trade reference assets and futures, launch tokens, and manage concentrated-liquidity pools under prescriptive adversarial roles. We analyze eight 72-cycle trajectories across two time-blinded hourly replay paths, with a runner-side wallet policy enabled or disabled. The retained artifacts connect generated outgoing messages, policy events, balances, positions, and cycle-end market state. A focal reconstruction shows a launch--promotion--exit scenario realized across private coordination, public claims, follower positioning, repeatedly withheld exits, and a later non-blocking request aligned with a token balance change. Across policy-enabled runs, the gate withholds direct requests selectively; most policy-categorized candidates are flagged rather than blocked, while the surrounding interaction can continue. Repeated runs also show that category-level and within-trajectory relations can recur even when normalized score-change rankings do not. These findings motivate agent-behavior evaluation that links communication, authorization, and evolving state instead of treating individual transaction verdicts as complete safety judgments.