DeFiFlowBench: Benchmarking and Improving Safe Executability in Natural-Language DeFi Workflow Synthesis

📅 2026-09-10
📈 Citations: 0
Influential: 0
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🤖 AI Summary
研究通过引入DeFiFlowBench和提出Koan-Safe方法,旨在解决自然语言合成的DeFi工作流中的安全性问题,提高安全执行能力。
📝 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.
Problem

Research questions and friction points this paper is trying to address.

DeFi
natural-language workflow synthesis
safe executability
Innovation

Methods, ideas, or system contributions that make the work stand out.

DeFiFlowBench
Koan-Safe
natural-language DeFi workflow synthesis
safe executability
EVM
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