Welcome to the resource topic for 2024/1834
Title:
Scutum: Temporal Verification for Cross-Rollup Bridges via Goal-Driven Reduction
Authors: Yanju Chen, Juson Xia, Bo Wen, Kyle Charbonnet, Hongbo Wen, Hanzhi Liu, Yu Feng
Abstract:Scalability remains a key challenge for blockchain adoption. Rollups—especially zero-knowledge (ZK) and optimistic rollups—address this by processing transactions off-chain while maintaining Ethereum’s security, thus reducing gas fees and improving speeds. Cross-rollup bridges like Orbiter Finance enable seamless asset transfers across various Layer 2 (L2) rollups and between L2 and Layer 1 (L1) chains. However, the increasing reliance on these bridges raises significant security concerns, as evidenced by major hacks like those of Poly Network and Nomad Bridge, resulting in losses of hundreds of millions of dollars. Traditional security analysis methods such as static analysis and fuzzing are inadequate for cross-rollup bridges due to their complex designs involving multiple entities, smart contracts, and zero-knowledge circuits. These systems require reasoning about temporal sequences of events across different entities, which exceeds the capabilities of conventional analyzers.
In this paper, we introduce a scalable verifier to systematically assess the security of cross-rollup bridges. Our approach features a comprehensive multi-model framework that captures both individual behaviors and complex interactions using temporal properties. To enhance scalability, we approximate temporal safety verification through reachability analysis of a graph representation of the contracts, leveraging advanced program analysis techniques. Additionally, we incorporate a conflict-driven refinement loop to eliminate false positives and improve precision. Our evaluation on mainstream cross-rollup bridges, including Orbiter Finance, uncovered multiple zero-day vulnerabilities, demonstrating the practical utility of our method. The tool also exhibited favorable runtime performance, enabling efficient analysis suitable for real-time or near-real-time applications.
ePrint: https://eprint.iacr.org/2024/1834
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