AI and Blockchain in Web3 Security: Discovering a New Horizon of Possibilities

AI and Blockchain are two powerful terms that have revolutionized the technology world.
They were once considered separate domains, but not anymore. The space of decentralized finance (DeFi) security is where these technologies have converged and created a synergy. This article will explore how these technologies can build a secure and robust foundation for DeFi's future.
Audit as an essential procedure
As you probably know, Web3 faces serious security challenges. In just the first quarter of 2023, hackers stole $265 million in 22 cyberattacks. They target different layers, from the protocol layer, where they try to break into the smart contract, to the application layer, where they use several scam schemes like phishing and identity theft to harm users.
Even the infrastructure layer, where the nodes and the blockchain foundations are, is unsafe. But the developers who want to launch applications must prioritize the protocol layer and get thorough audits.
AI and Blockchain scheme
An audit is a careful and systematic process of checking the blockchain code for its safety and integrity.
Through this process, the expert auditors find possible weaknesses, thus making the protocol more resistant to external attacks. And, of course, the auditors use the best tools to boost confidence in the protocol's security.

For instance, automated code analyzers are one of the tools to apply. They usually use standard methods to scan for vulnerabilities in conventional terms. A popular tool in this area is Slither, a static analysis framework for smart contracts, which can detect common vulnerabilities that can endanger the system.

But technology keeps advancing, and the boundaries of what is possible keep shifting. AI (Artificial Intelligence) and ML (Machine Learning) techniques in auditing are becoming more popular because they can handle and examine vast amounts of data with a speed and accuracy that humans can hardly match.
Because smart contract code can be treated as a unique type of conversational language, it can be parsed using Natural Language Processing (NLP), a subset of AI/ML techniques. Thus, these systems can verify from the logic of the contract that the mathematical equations that govern a liquidity fund have been correctly reflected in the code.

Therefore, some security agents, such as Blaize, are already betting on using AI for blockchain audits, active protection measures, and early threat detection.

Yet, while AI-powered approaches are promising, they can be considered in their infancy compared to human expertise. Thus, its implementation must still be overseen by experienced blockchain security specialists to ensure its effectiveness.

Even so, the development of AI promises many advances in blockchain audit processes, and experts are keen to take advantage of them, evidencing that in the future, audits powered by AI could become the norm.
Protocol security doesn’t end with the audit
As we said above, a comprehensive audit must be performed before launching a blockchain protocol to identify and correct vulnerabilities.
But once in the market, the protocol is exposed to a hostile and changing environment, where attackers seek to exploit any weakness.

The protocol needs an extra layer of active protection that works in real-time to address these threats. This involves monitoring, detecting, analyzing, alerting, pausing, and evaluating transactions and protocol performance. AI is the ideal tool for this task, as it can process and analyze large amounts of blockchain-generated data quickly and accurately. Also, it can automate anomaly detection and enable more agile responses, reducing the impact of a potential breach.

Besides, this technology strengthens the protocol's security and prepares it for the uncertainties of the web landscape. Thus, in addition to the initial audit, continuous active protection, especially AI-based, can ensure a robust and resilient blockchain protocol capable of surviving day-to-day challenges.
How active protection is used
Blockchain transactions generate a large amount of data that is difficult to manage manually, but they also offer an opportunity to perform deep analysis and draw valuable conclusions. Here are some of how AI and ML technology are game changers in the blockchain security field:
Detecting irregularities in incoming transactions
Attackers often use test transactions with small amounts or a series of failed transactions to identify common protocol vulnerabilities. AI is an excellent tool to identify them by analyzing transaction patterns and alerting them to potential risks.
Analysis of the origin of the operation
Before a large-scale attack, hackers usually rehearse. This is why keeping track of suspicious addresses interacting with the protocol or executing pending transactions in the mempool is essential. Therefore, IA can be a powerful tool to speed up the process of analyzing implemented contracts, interaction with mixers (which may indicate illicit activities), tangled transfers, multiple protocol interactions, and chains of swaps and conversions.
Prompt response
Minimizing the gap between when a threat is detected and addressed is crucial to minimize potential damage. Among the factors that an AI system can evaluate are block load (an increase in this factor can indicate a possible attack), any suspicious activity around non-fungible tokens (NFT), dust attacks, changes in gas prices, and MEV transactions.
Thus, ML models can be trained to generate alerts based on specific parameters. While the actual models are complex, even a simple ML model, such as a decision tree, can provide valuable information when combined with input parameters processed through regression models.

CyVerse, for example, is a service that already leverages AI-driven models in the field. The VigiLens product integrates AI technologies to provide real-time threat intelligence, vulnerability management, and incident response capabilities, highlighting the immense potential of AI in blockchain security.
Enhancing blockchain security with AI active defense
But the uses of AI in blockchain security continue beyond basic transaction analysis and early detection of potential threats. Some other uses of this technology that security experts recognize are:
AI and Blockchain active protection
  • 1
    Rugpull protection
    Artificial intelligence can prevent this by analyzing transactions and detecting rare money movements.
  • 2
    User protection
    AI can help protect protocol users from being tricked by phishing by analyzing transaction sources.
  • 3
    Validator behavior review
    AI can help review the actions of validators, detect possible misbehavior, and generate alerts immediately.
  • 4
    Bridge protection
    AI can help protect bridges by examining signed messages and bridge interaction patterns and early warning of large withdrawal requests.
These tools will thus become essential in ensuring the integrity and security of Web3 protocols. Before we know it, they will become an everyday and indispensable element of the DeFi world.
About Blaize

Blaize has been working on AI/ML expertise for the last couple of years and has several certified specialists onboard. So Blaize fully supports the advice, and the Security team actively uses AI technologies during specific auditing rounds.

Blaize is a Ukrainian blockchain development and security company with a successful track record of over 50 audits just for the first half of 2023, including 2 comprehensive audits for Everstake. This company is listed on Alchemy’s security list and is a member of the DeFi Security Alliance, among other achievements.
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