Secure Smart Contract with Control Flow Integrity

• URL: http://arxiv.org/abs/2504.05509v1
• Date: Mon, 07 Apr 2025 21:08:16 GMT
• Title: Secure Smart Contract with Control Flow Integrity
• Authors: Zhiyang Chen, Sidi Mohamed Beillahi, Pasha Barahimi, Cyrus Minwalla, Han Du, Andreas Veneris, Fan Long,
• Abstract summary: We develop CrossGuard, a framework that enforces control flow integrity in real-time to secure smart contracts.<n>Our evaluation demonstrates that CrossGuard effectively blocks 28 of the 30 analyzed attacks when configured only once prior to contract deployment.
• Score: 3.1655211232629563
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Smart contracts power decentralized financial (DeFi) services but are vulnerable to complex security exploits that can lead to significant financial losses. Existing security measures often fail to adequately protect these contracts due to the composability of DeFi protocols and the increasing sophistication of attacks. Through a large-scale empirical study of historical transactions from the 30 hacked DeFi protocols, we discovered that while benign transactions typically exhibit a limited number of unique control flows, in stark contrast, attack transactions consistently introduce novel, previously unobserved control flows. Building on these insights, we developed CrossGuard, a novel framework that enforces control flow integrity in real-time to secure smart contracts. Crucially, CrossGuard does not require prior knowledge of specific hacks; instead, it dynamically enforces control flow whitelisting policies and applies simplification heuristics at runtime. This approach monitors and prevents potential attacks by reverting all transactions that do not adhere to the established control flow whitelisting rules. Our evaluation demonstrates that CrossGuard effectively blocks 28 of the 30 analyzed attacks when configured only once prior to contract deployment, maintaining a low false positive rate of 0.28% and minimal additional gas costs. These results underscore the efficacy of applying control flow integrity to smart contracts, significantly enhancing security beyond traditional methods and addressing the evolving threat landscape in the DeFi ecosystem.

Related papers

• Securing Legacy Communication Networks via Authenticated Cyclic Redundancy Integrity Check [98.34702864029796]
  We propose Authenticated Cyclic Redundancy Integrity Check (ACRIC) ACRIC preserves backward compatibility without requiring additional hardware and is protocol agnostic. We show that ACRIC offers robust security with minimal transmission overhead ( 1 ms)
  arXiv  Detail & Related papers  (2024-11-21T18:26:05Z)
• PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning [49.916365792036636]
  Federated learning (FL) has recently gained significant momentum due to its potential to leverage large-scale distributed user data. The transmitted model updates can potentially leak sensitive user information, and the lack of central control of the local training process leaves the global model susceptible to malicious manipulations on model updates. We develop a general framework PriRoAgg, utilizing Lagrange coded computing and distributed zero-knowledge proof, to execute a wide range of robust aggregation algorithms while satisfying aggregated privacy.
  arXiv  Detail & Related papers  (2024-07-12T03:18:08Z)
• A Language for Smart Contracts with Secure Control Flow (Technical Report) [2.8771104250726847]
  Smart contracts are vulnerable to control-flow attacks based on confused deputies, reentrancy, and incorrect error handling. We introduce SCIF, a language for secure smart contracts, that addresses these classes of control-flow attacks. SCIF enforces both classic end-to-end information flow security and new security restrictions on control flow, even when SCIF contracts interact with malicious non-SCIF code.
  arXiv  Detail & Related papers  (2024-07-01T11:51:21Z)
• A Survey and Comparative Analysis of Security Properties of CAN Authentication Protocols [92.81385447582882]
  The Controller Area Network (CAN) bus leaves in-vehicle communications inherently non-secure. This paper reviews and compares the 15 most prominent authentication protocols for the CAN bus. We evaluate protocols based on essential operational criteria that contribute to ease of implementation.
  arXiv  Detail & Related papers  (2024-01-19T14:52:04Z)
• LookAhead: Preventing DeFi Attacks via Unveiling Adversarial Contracts [15.071155232677643]
  Decentralized Finance (DeFi) incidents have resulted in financial damages exceeding 3 billion US dollars.<n>Current detection tools face significant challenges in identifying attack activities effectively.<n>We propose a new framework for effectively detecting DeFi attacks via unveiling adversarial contracts.
  arXiv  Detail & Related papers  (2024-01-14T11:39:33Z)
• Blockchain Smart Contract Threat Detection Technology Based on Symbolic Execution [0.0]
  Reentrancy vulnerability, which is hidden and complex, poses a great threat to smart contracts. In this paper, we propose a smart contract threat detection technology based on symbolic execution. The experimental results show that this method significantly increases both detection efficiency and accuracy.
  arXiv  Detail & Related papers  (2023-12-24T03:27:03Z)
• Gradual Verification for Smart Contracts [0.4543820534430522]
  Algos facilitate secure resource transactions through smart contracts, yet these digital agreements are prone to vulnerabilities. Traditional verification techniques fall short in providing comprehensive security assurances. This paper introduces an incremental approach: gradual verification.
  arXiv  Detail & Related papers  (2023-11-22T12:42:26Z)
• G$^2$uardFL: Safeguarding Federated Learning Against Backdoor Attacks through Attributed Client Graph Clustering [116.4277292854053]
  Federated Learning (FL) offers collaborative model training without data sharing. FL is vulnerable to backdoor attacks, where poisoned model weights lead to compromised system integrity. We present G$2$uardFL, a protective framework that reinterprets the identification of malicious clients as an attributed graph clustering problem.
  arXiv  Detail & Related papers  (2023-06-08T07:15:04Z)
• HighGuard: Cross-Chain Business Logic Monitoring of Smart Contracts [2.2375489356775464]
  HighGuard is a tool to detect transactions that violate business logic specifications of smart contracts. It is capable of operating in a cross-chain environment for detecting business logic flaws across different blockchain platforms. Our evaluation, involving 54 exploits, confirms HighGuard's effectiveness in detecting business logic vulnerabilities.
  arXiv  Detail & Related papers  (2023-05-14T21:33:19Z)
• Certifiers Make Neural Networks Vulnerable to Availability Attacks [70.69104148250614]
  We show for the first time that fallback strategies can be deliberately triggered by an adversary. In addition to naturally occurring abstains for some inputs and perturbations, the adversary can use training-time attacks to deliberately trigger the fallback. We design two novel availability attacks, which show the practical relevance of these threats.
  arXiv  Detail & Related papers  (2021-08-25T15:49:10Z)
• ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning [80.85273827468063]
  Existing machine learning-based vulnerability detection methods are limited and only inspect whether the smart contract is vulnerable. We propose ESCORT, the first Deep Neural Network (DNN)-based vulnerability detection framework for smart contracts. We show that ESCORT achieves an average F1-score of 95% on six vulnerability types and the detection time is 0.02 seconds per contract.
  arXiv  Detail & Related papers  (2021-03-23T15:04:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.