Lightning Cat’s recent publication unveiled its AI model with capabilities to detect and resolve blockchain vulnerabilities that hackers and bots could exploit. The publication acknowledged the critical input that smart contracts play in the blockchain industry, particularly in running meme coins and supporting complex decentralized finance (DeFi) platforms.
Lightning Cat Leveraging Deep Learning Techniques to Detect Vulnerabilities
Lightning Cat’s report reveals that automated programs often face persistent threats posed by cyberattacks often causing huge financial and reputational losses. The researchers consider that the best defense to the vulnerabilities is artificial intelligence.
Lightning Cat involves a novel solution leveraging deep learning techniques to detect vulnerabilities in smart contracts. Its capabilities outlined in the Scientific Reports publication are nurtured via training in three deep learning models, including OptimizedCodeBERT, Optimized-LSTM, and Optimized-CNN.
Lightning Cat overcomes the inadequacies of conventional analytical tools that result in false positives and negatives. Instead, it uses deep learning methods to spot possible vulnerabilities with precision as if trained in Solidity programming language.
Lightning Cat Outperforming Static Detection Tools
The researchers illustrated that the proposed method yields reasonable data preprocessing without compromising the model optimization. It results in improved detection performance. The three models undergo detailed training using data sets with thousands of vulnerable contracts.
Lightning Cat researchers hail the CodeBERT model as one outperforming the static detection tools with an impressive f1-score at 93.53%. It accurately captured the syntax and semantics of the code, thereby proving the potential to audit blockchain.
Lightning Cat Double-Edged Sword
Lightning Cat, however, suffers some vulnerabilities from several risks. The researchers identified it as a “double-edged sword”. The researchers admitted that while beneficial in enhancing smart contract security, bad actors would exploit its capabilities to detect the bugs for easier exploitation.
To resolve the vulnerability of Lightning Cat, researchers urged coders to prioritize proper security practices and audit their products regularly. Developers should audit the code regularly, besides completing the secure coding training and adopting responsible vulnerability disclosure policies.
The researchers warn developers to notify the relevant entities and individuals privately. They indicated that the smart contract had suffered multiple breaches, necessitating the Lightning Cat work.
The researchers cited the 2016 attack on the DAO with exploiters targeting the reentrancy vulnerability, making away with Ethereum worth $60 million. The exploit prompted a split on the Ethereum blockchain.
The BEC smart contract suffered a similar incident in 2018 following an integer overflow vulnerability. It caused the token value to plunge to zero, disrupting the market.
AI-Powered Lightning Cat Reinforcing Software Security to Avert the DeFi Exploits
Lightning Cat is useful for developers in assessing their tools before deployment. It suits resolving the vulnerabilities portrayed by DeFi exploits.
Halborn chief operating executive David Schwed believed in the capability to avert the DeFi exploits through proper security checks.
Schwed added that multiple of the hacks were not entirely from on-chain vulnerabilities. He said the vulnerability surfaced in standard Web2 infrastructure due to poor security practices.
The Lightning Cat initiative leverages AI to detect code vulnerabilities. Such constitute part of the broader trend in the AI-blockchain technologies convergence to reinforce software security.
The Lightning Cat embraces this trend to integrate AI power alongside the blockchain-based system to test decentralized software. Doing so taps the power of deep learning founded upon blockchain technologies’ reliability and transparency.
Lightning Cat Initiative Enhances Code Development Security
Proponents of AI-blockchain technology integration consider the approach as accelerating the vulnerability detection process. They consider the approach as beneficial within the remote work scenarios.
The Lightning Cat model features the InterPlanetary File System (IPFS) to guarantee efficient data storage. Also, the IPFS presents a comprehensive solution to enhance code development security. Its interoperability made the Lightning Cat facilitate testing for vulnerability in various decentralized environments.