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USCSA: Evolution-Aware Security Analysis for Proxy-Based Upgradeable Smart Contracts

Xiaoqi Li, Lei Xie, Wenkai Li, Zongwei Li

TL;DR

USCSA introduces an evolution-aware framework for security analysis of proxy-based upgradable smart contracts by combining AST differential analysis with a multi-module pipeline that maps code changes to vulnerabilities. It achieves high accuracy (≈92% precision, ≈90% F1) in detecting upgrade-induced vulnerabilities across 3,546 cases and reports a 30% efficiency gain in prioritizing high-risk changes. The approach integrates Upgrade Path Tracing, AST Difference Analysis, static vulnerability detection, and a novel Change-Vulnerability Matching, augmented by LLM-assisted causality analysis to explain risk evolution and provide remediation guidance. The results demonstrate strong detection performance and offer a reproducible audit process, with plans to broaden applicability to other blockchains and domains like DeFi and NFTs.

Abstract

In the case of upgrading smart contracts on blockchain systems, it is essential to consider the continuity of upgrade and subsequent maintenance. In practice, upgrade operations often introduce new vulnerabilities. To address this, we propose an Upgradable Smart Contract Security Analyzer, USCSA, which evaluates the risks associated with the upgrade process using the Abstract Syntax Tree (AST) differential analysis. We collected and analyzed 3,546 cases of vulnerabilities in upgradable contracts,covering common vulnerability categories such as reentrancy, access control flaws, and integer overflow. Experimental results show that USCSA achieves an accuracy of 92.3%, recall of 89.7%, and F1-score of 91.0% in detecting upgrade-induced vulnerabilities. In addition, the efficiency of mapping high-risk changes has achieved a 30% improvement over the conventional approach. As a result, USCSA provides a significant advantage to improve the security and integrity of upgradable smart contracts, providing a novel and efficient solution to secure audits on blockchain applications.

USCSA: Evolution-Aware Security Analysis for Proxy-Based Upgradeable Smart Contracts

TL;DR

USCSA introduces an evolution-aware framework for security analysis of proxy-based upgradable smart contracts by combining AST differential analysis with a multi-module pipeline that maps code changes to vulnerabilities. It achieves high accuracy (≈92% precision, ≈90% F1) in detecting upgrade-induced vulnerabilities across 3,546 cases and reports a 30% efficiency gain in prioritizing high-risk changes. The approach integrates Upgrade Path Tracing, AST Difference Analysis, static vulnerability detection, and a novel Change-Vulnerability Matching, augmented by LLM-assisted causality analysis to explain risk evolution and provide remediation guidance. The results demonstrate strong detection performance and offer a reproducible audit process, with plans to broaden applicability to other blockchains and domains like DeFi and NFTs.

Abstract

In the case of upgrading smart contracts on blockchain systems, it is essential to consider the continuity of upgrade and subsequent maintenance. In practice, upgrade operations often introduce new vulnerabilities. To address this, we propose an Upgradable Smart Contract Security Analyzer, USCSA, which evaluates the risks associated with the upgrade process using the Abstract Syntax Tree (AST) differential analysis. We collected and analyzed 3,546 cases of vulnerabilities in upgradable contracts,covering common vulnerability categories such as reentrancy, access control flaws, and integer overflow. Experimental results show that USCSA achieves an accuracy of 92.3%, recall of 89.7%, and F1-score of 91.0% in detecting upgrade-induced vulnerabilities. In addition, the efficiency of mapping high-risk changes has achieved a 30% improvement over the conventional approach. As a result, USCSA provides a significant advantage to improve the security and integrity of upgradable smart contracts, providing a novel and efficient solution to secure audits on blockchain applications.

Paper Structure

This paper contains 15 sections, 1 equation, 3 figures, 2 tables, 1 algorithm.

Table of Contents

  1. INTRODUCTION
  2. BACKGROUNDS
  3. Smart Contracts and Security Audits
  4. Upgradable Smart Contracts
  5. Related Work
  6. METHODOLOGY
  7. Upgrade Path Tracing Module
  8. AST Difference Analysis Module
  9. Static Vulnerability Detection Module
  10. Change-Vulnerability Matching Module
  11. LLM-assisted “Change-Vulnerability” Causality Matching
  12. RESULT
  13. Dataset
  14. Performance and Evaluation
  15. Discussion and Future Plans

Figures (3)

  • Figure 1: USCSA Overall Framework Diagram.
  • Figure 2: LLM-Assisted Analysis Prompt.
  • Figure 3: USCSA Test results.