USCSA Tool Achieves Over 90% Accuracy in Detecting Upgrade-Induced Smart Contract Vulnerabilities

Global: USCSA Tool Achieves Over 90% Accuracy in Detecting Upgrade-Induced Smart Contract Vulnerabilities

Researchers Xiaoqi Li, Lei Xie, Wenkai Li, and Zongwei Li released a new security analyzer, USCSA, on arXiv on December 9 2025 (revised December 25 2025) to evaluate risks introduced during the upgrade of proxy‑based smart contracts. The tool applies abstract syntax tree (AST) difference analysis to identify vulnerabilities that emerge when contracts are upgraded, reporting an overall accuracy of 92.3%, recall of 89.7%, and an F1‑score of 91.0%.

Background on Upgradeable Smart Contracts

Upgradeable contracts allow developers to modify contract logic without redeploying a new address, preserving state and user interactions. While this flexibility supports continuous improvement, each upgrade can unintentionally expose new attack surfaces, such as reentrancy loops, flawed access controls, or integer overflows.

Methodology: AST Difference Analysis

USCSA constructs AST representations of both the original and upgraded contract versions, then computes structural differences to pinpoint code changes that correlate with known vulnerability patterns. The approach isolates high‑risk modifications, enabling auditors to focus on the most critical sections.

Dataset and Vulnerability Categories

The authors compiled a corpus of 3,546 documented upgrade‑induced vulnerability instances drawn from public repositories and prior audit reports. The dataset spans common categories—including reentrancy, access‑control flaws, and integer overflow—and serves as the benchmark for evaluating USCSA’s detection capabilities.

Performance Results

Experimental evaluation shows USCSA correctly identifies 92.3% of the vulnerable upgrades, with a recall of 89.7% and an F1‑score of 91.0%. In addition, the tool reduces the time required to map high‑risk changes by roughly 30% compared with traditional static‑analysis pipelines.

Comparison with Existing Approaches

Compared to conventional security scanners that analyze contracts in isolation, USCSA’s change‑aware analysis captures the dynamic impact of upgrades. The reported efficiency gain suggests that auditors can achieve broader coverage without proportionally increasing manual review effort.

Implications for Blockchain Security

By automating the detection of upgrade‑related flaws, USCSA offers a scalable solution for developers and security firms seeking to maintain the integrity of evolving decentralized applications. The tool’s high precision may help reduce the incidence of post‑upgrade exploits that have historically led to significant financial losses.

Future Directions

The authors propose extending the framework to support additional proxy patterns and integrating machine‑learning classifiers to further refine vulnerability prediction. Broader adoption could standardize upgrade‑risk assessment across blockchain platforms.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.