Inspiration

Mission and Story

Let’s explore these three famous smart contract hacks. The mission of BugStrike! Is to contribute efforts in Blockchain security on preventing such vulnerabilities:

The DAO Hack:

Incident: The DAO (Decentralized Autonomous Organization) was a venture capital fund built on Ethereum. In 2016, attackers exploited a combination of vulnerabilities in The DAO’s smart contract, resulting in the theft of approximately $50 million worth of Ether.

Yearn Finance Misconfiguration:

Incident: In 2023, Yearn Finance suffered a loss of nearly $11.6 million due to a misconfiguration in the yUSD token’s smart contract.

Flash Loan Manipulation (Hundred Finance):

Incident: Hundred Finance fell victim to a flash loan attack, where an attacker exploited the contract’s logic to manipulate funds.

What it does

BugStrike has already made contributive efforts and remains dedicated to help fight off cybersecurity threats:

Automated Scanning: BugStrike! can actively scan vulnerabilities, identifying the vulnerable portions and alerting developers.

Static Analysis: BugStrike! performs static analysis to detect reentrancy vulnerabilities.

Educational Outreach: BugStrike! will be open source to developers, teaching best practices for secure smart contract development. This knowledge helps prevent similar incidents.

In summary, BugStrike will play a role in securing smart contracts by offering automated scanning, education, and ongoing monitoring. Its proactive approach helps prevent financial losses and ensures the integrity of decentralized ecosystems.

How we built it

The Bugstrike took days of research and Development to complete. Using HGAT: Smart Contract Vulnerability Detection Method Based on Hierarchical Graph Attention Network.

Hierarchical Graph Attention Network (HGAT) Model

BugStrike will leverage the HGAT model, which combines abstract syntax trees (ASTs) and control flow graphs (CFGs) to represent smart contract functions. The following steps outline the approach:

AST and CFG Abstraction: Transform smart contract functions into code graphs. Node Feature Extraction: Extract features from each node in the code subgraph. Graph Attention Mechanism (GAT): Utilize GAT to enhance feature representation. Statement-Level Features: Splice vectors to form features for each line of statements. Vulnerability Detection: Use these features to detect vulnerabilities.

Challenges we ran into

Complexity of Smart Contracts: The scanner has to be able to handle more complexities of smart contracts consisting of multiple functions, dependencies, and interactions. Using techniques like symbolic execution and intermediate representation (IR) help navigate this complexity.

False Positives and False Negatives: The scanner should minimize false positives by using precise detection techniques (e.g., formal verification).

Adaptability to New Vulnerabilities: As new vulnerabilities emerge, regular updates, community contributions, and integration with security advisories keep the scanner up-to-date.

Accomplishments that we're proud of

I am proud of building this vulnerability scanner. This is a massive accomplishment as I've completed a Javascript and Solidity scanner that would help provide security. As an aspiring Cybersecurity engineer I hope to complete more projects like this one.

What we learned

HGAT: Smart Contract Vulnerability Detection Method Based on Hierarchical Graph Attention Network

Abstract

With the widespread adoption of blockchain technology, smart contracts have become integral components of decentralized applications. However, their internal logic is increasingly sophisticated, making them susceptible to vulnerabilities. Existing detection methods suffer from high false positive rates and low accuracy, necessitating human intervention for secondary detection. In this paper, we propose HGAT (Hierarchical Graph Attention Network), a novel detection model specifically designed to address these challenges and improve smart contract vulnerability detection.

  1. Introduction

Blockchain technology, through its consensus process, enables secure and decentralized communication among nodes without relying on a central authority. Smart contracts, operating as applications atop the blockchain layer, facilitate various transactions, including virtual currency exchanges. However, flaws in smart contract code can lead to significant financial losses and security breaches. Notable incidents, such as the attack on The DAO, the misconfiguration in Yearn Finance, and flash loan manipulation, underscore the urgency of robust vulnerability detection mechanisms1.

  1. HGAT: Methodology

2.1 Abstraction and Feature Extraction

Abstract Syntax Tree (AST) and Control Flow Graph (CFG): We abstract smart contract functions into code graphs using AST and CFG representations.Each node in the code subgraph corresponds to a specific statement or control flow element.

Node Feature Extraction: Extract features from each node in the code subgraph.These features capture syntactic and semantic information relevant to vulnerability detection.

2.2 Graph Attention Mechanism (GAT)

Graph Attention Network (GAT): We utilize GAT to enhance feature representation. GAT assigns different attention weights to neighboring nodes, capturing context-aware information.

Statement-Level Features: Splice the obtained vectors from GAT to form features for each line of statements.These features encode both local and global context.

2.3 Vulnerability Detection

Feature-Based Detection: We use the extracted features to detect vulnerabilities. HGAT identifies patterns associated with common vulnerabilities (e.g., reentrancy, integer overflow).

Evaluation and Performance: We assess HGAT using an open-source smart contract vulnerability sample dataset. Experimental results demonstrate that HGAT outperforms other detection techniques in terms of accuracy and efficiency.

  1. Conclusion

The BugStrike Smart Contract Vulnerability Scanner, based on HGAT, represents a significant advancement in securing decentralized ecosystems. By automating vulnerability detection, providing educational resources, and continuously monitoring deployed contracts, BugStrike contributes to the integrity and trustworthiness of smart contracts. As the blockchain landscape evolves, robust security measures like HGAT become essential for safeguarding digital assets and ensuring the long-term viability of decentralized applications.

What's next for BugStrike - smart contract vulnerability scanner

BugStrike has already made contributive efforts and remains dedicated to help fight off cybersecurity threats:

Automated Scanning: BugStrike! can actively scan vulnerabilities, identifying the vulnerable portions and alerting developers.

Static Analysis: BugStrike! performs static analysis to detect reentrancy vulnerabilities.

Educational Outreach: BugStrike! will be open source to developers, teaching best practices for secure smart contract development. This knowledge helps prevent similar incidents.

In summary, BugStrike will play a role in securing smart contracts by offering automated scanning, education, and ongoing monitoring. Its proactive approach helps prevent financial losses and ensures the integrity of decentralized ecosystems.

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