PSR2: A Phase-based Semantic Reasoning Framework for Atomicity Violation Detection via Contract Refinement

2026-04-08

AI Summary

This study addresses the high false positive and false negative rates in existing static analysis tools for detecting atomicity violations in smart contracts, which stem from insufficient context awareness and inadequate modeling of intermediate states. To overcome these limitations, the authors propose PSR², a novel framework that integrates control flow graphs and abstract syntax trees to construct a unified model of atomicity inconsistencies. PSR² employs a graph-structure analysis module to identify suspicious execution paths, a semantic context analysis module to extract data dependencies, and a fusion decision module that performs formal cross-validation. Evaluated on 1,600 real-world smart contracts, PSR² achieves an F1-score of 94.69%, substantially outperforming baseline tools (51.86%). Ablation studies further confirm that its fusion mechanism reduces false positives by nearly 50%.

Abstract

With the rapid advancement of decentralized applications, smart contract security faces severe challenges, particularly regarding atomicity violations in complex logic such as Oracle and NFT contracts. Rigid rule sets often limit traditional static analyzers and lack deep contextual awareness, leading to high false-positive and false-negative rates when identifying vulnerabilities that depend on intermediate state inconsistencies. To address these limitations, this paper proposes PSR\textsuperscript{2}, a novel collaborative static analysis framework that integrates structural path searching with deterministic semantic reasoning. PSR\textsuperscript{2} utilizes a Graph Structure Analysis Module (GSAM) to identify suspicious execution sequences in control flow graphs and a Semantic Context Analysis Module (SCAM) to extract data dependencies and state facts from abstract syntax trees. A Fusion Decision Module (FDM) then performs formal cross validation to confirm vulnerabilities based on a unified atomicity inconsistency model. Experimental results on 1,600 contract samples demonstrate that PSR\textsuperscript{2} significantly outperforms pattern-matching baselines, achieving an F1-score of 94.69\% in complex ERC-721 scenarios compared to 51.86\% for existing tools. Ablation studies further confirm that our fusion logic effectively reduces the false-positive rate by nearly half compared to single module analysis.

Problem

• atomicity violation
• smart contract security
• static analysis
• false positives
• intermediate state inconsistency

Innovation

• atomicity violation
• smart contract security
• static analysis
• semantic reasoning
• control flow graph