Seedlabs

Cross-Function Reentrancy Audit Scanner for Deployed Ethereum Contracts

A scanning service that replays a smart contract's real on-chain transaction history through EVM-trace Datalog rules and delivers an audit report flagging cross-function reentrancy behaviors that single-function detectors miss.

Computer ScienceBlockchain Technology Applications and Security
AI Governance and Cognitive ImpactSmart contract security auditing and DeFi protocol risk assessment

Concept

A SaaS audit product for deployed Ethereum contracts. A customer — an audit firm preparing an engagement, a DeFi protocol reviewing itself, or an insurer pricing risk — submits one or more contract addresses. The service pulls those contracts' on-chain transaction history, extracts EVM execution traces with a trace-extraction component modernized for recent Ethereum client versions and current EVM instructions, and runs Datalog-based detection rules purpose-built for cross-function reentrancy: attacks where the re-entrant call lands in a different function of the same contract than the one that made the external call, so single-function analyzers never see the pattern. The deliverable is a report listing every detected cross-function reentrancy behavior, the function pair involved, the triggering transactions, and a plain-language risk explanation — or a clean certificate when none is found. The product is explicitly positioned as behavioral evidence ("what actually executed on-chain") that complements static analysis, not a substitute for it.

Why now

The new paper demonstrates, on real Ethereum on-chain transaction traces, that Datalog rules over EVM traces detect cross-function reentrancy behaviors the original TxSpector rules could not capture — closing a known detection gap at prototype level. Just as importantly for commercialization, the paper modernized the trace-extraction component to recent Ethereum client versions and updated EVM instructions, which is what makes the pipeline runnable against today's chain. The stated limitations size the product honestly: the method only analyzes executed paths, so it is sold as a forensic/behavioral audit of live contracts (what has actually happened on-chain) rather than a complete vulnerability verifier, augmenting rather than replacing static tools.

Written by GLM · 10 Oct 2026

AI assessment

Backed by 1 paper93

A highly focused forensic security tool that leverages a specific research breakthrough to detect a known blind spot in smart contract auditing.

Evidence strength
5/5
The idea directly implements the paper's core contribution—modernized trace extraction and new Datalog rules—without overclaiming the tool's ability to find unexecuted paths.
Market pull
4/5
High-value beneficiaries like Nexus Mutual and audit firms have a strong financial incentive to detect complex reentrancy that static analysis misses.
Novelty & moat
5/5
The idea addresses a specific technical gap (cross-function reentrancy) and is entirely distinct from the unrelated ideas in the catalog.
Feasibility
4/5
The research provides the prototype and the modernized trace-extraction pipeline, making the path to an MVP straightforward for a technical team.
Wedge clarity
5/5
The wedge is extremely sharp: a behavioral audit of deployed contracts specifically for cross-function reentrancy.
Simplicity / focus
5/5
The product is a single-purpose scanner with a clear input (contract address) and output (risk report), avoiding platform bloat.

Scored by Gemma 4 · 10 Oct 2026. Rated against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity), relative to the closest ideas already in the catalog. A prior estimate to compare ideas before real-world signal arrives.

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Who benefits

  • Trail of Bitscompany

    Its blockchain audit practice can run this scanner as an automated first pass over a client's deployed contracts, catching cross-function reentrancy patterns that static tooling misses before an engagement begins.

  • ConsenSys Diligencecompany

    As a smart contract audit firm, it can offer trace-based behavioral audits as a new deliverable, differentiating its service with evidence of what actually executed on-chain.

  • Curve Financecompany

    Curve's 2023 Vyper reentrancy incident makes a purpose-built reentrancy scanner concretely relevant for self-review of its deployed pools before future incidents.

  • Nexus Mutualorganization

    The DeFi insurance mutual can feed scan results into underwriting and risk pricing for cover sold against specific protocols, replacing guesswork with observed on-chain reentrancy behavior.

  • Immuneficompany

    The bug bounty platform can use scan reports to prioritize bounty scopes and give whitehats trace-level evidence when triaging reentrancy submissions.

Research it builds on

  1. Detecting Cross-Function Reentrancy from EVM Traces
    Guesmi, Semia, Piazza, Carla, Gasparetto, Andrea et al. · 2026 · 150 citations
    All ideas from this paper →
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