AI & Blockchain: Active Protection for Your Web3 Project

By Pavlo Horbonos
08.08.2023

In the trustless, decentralized, and public environment of Web3, the blockchain space can sometimes feel like the Wild West. With an array of independent protocols and platforms, vast amounts of funds flowing between them, and all data being public and traceable, the need for robust security is paramount. At the foundation of this web3 world lies cryptography, establishing the main laws governing its functioning. However, to combat the various threats that exist, additional layers of protection are required, which is where web3 security providers like Blaize Security step in.

The application of AI/ML technology has begun to revolutionize the web3.0 security audit process, opening up new possibilities.

Does the problem of security really exist in the Web3 world? Let the numbers speak: as of the end of Q1 2023, there were 22 reported cybersecurity hacks totaling over $265 million in losses. The biggest single hack stole $197 million.

These threats encompass different layers – from the protocol layer, where malicious actors attempt to exploit smart contracts, to the application layer, where users must be vigilant against phishing attacks, identity theft, and more. Even the infrastructure layer faces numerous attack vectors that threaten the very foundations of blockchains and the mechanisms underpinning node functionality. Therefore, it is essential to focus on the protocol layer, where security starts with a thorough audit.

Blaize specialists have deep expertise in AI and ML solutions development and implementation. Learn more about how to enhance your business with the most trendy technologies.

What Covers Audit for the Protocol

Security audit is a must-have stage for ensuring the safety of blockchain protocols. It involves a meticulous and methodical examination of the blockchain code to ascertain its security and integrity. Through this process, s team of professional auditors identify and address potential vulnerabilities, thereby reinforcing the protocol’s resilience against external threats. And of course auditors use all modern tools they can possess to increase the confidence in protocol safety.

For example, the first set of tools to use are automated code analyzers. Though in conventional terms, they primarily use standardized techniques to probe for vulnerabilities. A well-known tool in this domain is Slither, a static analysis framework for smart contracts, which is well-equipped to detect traditional vulnerabilities that can jeopardize the system.

However, as technology evolves, the boundaries of what’s possible are continuously being pushed. The use of AI and ML techniques in auditing is gaining traction thanks to their ability to process and analyze vast amounts of data with a level of efficiency and accuracy that is challenging for humans to match.

Smart contracts’ code, akin to any form of language, follows a set of grammatical rules, and hence can be treated as a unique type of conversational ‘language’ (but between the developer and the virtual machine). Natural Language Processing (NLP), a subset of AI/ML techniques, can thus be utilized to analyze this ‘language’. For instance, NLP can be applied to confirm if the mathematical equations governing a liquidity pool have been correctly reflected in the code. Or that the code has “logical” logic flow. Moreover, the integration of sophisticated techniques such as neural networks and reinforcement learning into the auditing process can provide valuable insights and refine the efficiency of vulnerability detection.

However, it’s crucial to note that while these AI-driven approaches show promise, their implementation must be supervised by experienced blockchain security specialists. These professionals play a vital role in steering the model in the right direction, ensuring that it functions optimally within the complex dynamics of blockchain technology.

At this stage, the effectiveness of AI models like ChatGPT in the auditing process is still in the nascent stage when compared to a human auditor. AI-augmented auditing processes are not yet at a point where they can replace the manual, cross-verification methods traditionally employed by auditors.

Nevertheless, the continuous evolution of AI promises potential advancements in the blockchain auditing process. Auditors are keen on harnessing this transformative technology and are steadily integrating AI/ML-based tools into their arsenal. While we are yet to realize the full potential of AI in auditing, the signs are encouraging, suggesting a future where AI-powered audits could become the norm.

When the Protocol Needs More Protection

A comprehensive audit serves as a security foundation before deploying a blockchain protocol. It is during this stage where potential vulnerabilities are detected and rectified, preparing the protocol for launch. However, once the protocol is deployed, it faces an open environment — the ‘wild west’ of web3 — where it must fend off a myriad of potential malicious actors intending to exploit any weaknesses in the protocol.

A robust security audit coupled with a well-structured protocol architecture significantly minimizes the probability of a successful breach. Yet, the dynamic and unpredictable nature of the web3 environment warrants an additional layer of protection to keep up with evolving threats.

Active protection mechanisms serve as this additional security layer. They operate in real-time, providing ongoing safeguards against emerging threats. Active protection entails monitoring transactions, detecting anomalies, analyzing unprocessed transactions in the mempool, setting up alerts for suspicious activities, pausing the protocol under threat, and assessing the load on the protocol. These mechanisms enhance the resilience of the protocol by continually analyzing and responding to threats.

This is where AI is perfect — managing the massive blockchain-generated data. With thousands of transactions occurring simultaneously, it becomes an insurmountable task to track and analyze each transaction for potential threats manually. AI technologies, particularly machine learning algorithms, can automate this process, swiftly analyzing transactions in real time and detecting anomalies with high accuracy.

This AI-powered approach increases the efficiency and speed of threat detection and allows for quicker responses, minimizing the potential damage that a breach could cause. With AI at the helm, protocols can better manage the vast amount of data they deal with and reinforce their defenses against the uncertainties of the web3 landscape.

Therefore, while the initial security audit is a critical step in preparing the protocol for deployment, ongoing active protection strategies, especially those leveraging AI technologies, are equally crucial in maintaining the protocol’s security post-deployment. It’s a combination of these processes that assures a robust and resilient blockchain protocol, ready to tackle the challenges of the ‘wild west’ of web3.

How to Use Active Protection

The vast amount of data generated by blockchain transactions presents both a challenge and an opportunity. While the sheer volume of data can be overwhelming to manage manually, this transparency allows us to conduct in-depth analysis and draw meaningful conclusions. It’s here that AI and ML technologies are revolutionizing the field of blockchain security. Let’s explore how.

Incoming Transaction Pattern Analysis

Typically, hacks involve a series of transactions, including testing transactions with small amounts, and failed transactions probing for standard vulnerabilities. AI can be programmed to analyze these transaction patterns, detect irregularities, and flag potential threats.

Transaction Source Analysis

Sophisticated hackers often carry out numerous simulations before launching a full-scale attack. Therefore, the analysis of suspicious addresses interacting with the protocol or executing pending transactions in the mempool becomes critical. Here are some aspects that can be analyzed:

  • Contract Deployment: Whether the suspicious addresses have deployed any contracts.
  • Interaction with Mixers: The involvement of suspicious addresses with mixers can often hint at illicit activities.
  • Tangled Transfers: Multiple transfers to various addresses can indicate an attempt to confuse tracking mechanisms.
  • Multiple Protocol Interactions: Interactions with several protocols might suggest a more extensive, planned attack.
  • Chains of Swaps and Conversions: A series of swaps and conversions can signify attempts to mask the original source of funds.

These parameters and more can be analyzed using AI, which can quickly and efficiently process this information to detect anomalies.

Early Detection

The early detection of threats can be crucial in minimizing potential damages. AI-powered systems can monitor various factors such as:

  • Block Load: Unusual increase in the load of blocks could indicate a potential attack.
  • Suspicious Activities around NFTs: Any irregular patterns related to Non-Fungible Tokens (NFTs) can be flagged – for example, series of sell price changes, listings/delistings from auctions, or fake drops mimicking famous collections.
  • Dust Attacks: Rapid small transfers (or ‘dust’ attacks) can be detected and handled.
  • Gas Prices: Sudden changes in gas prices can be a signal of market manipulation attempts.
  • MEV Transactions: Backward analysis of Miner Extractable Value (MEV) transactions can reveal potential exploitations.

ML models can be trained to generate alerts based on specific sets of parameters. While the real models are complex, even a simple ML model such as a decision tree can offer valuable insights when combined with input parameters processed through regression models.

CyVerse, one of our partners, is a great example of a service already leveraging AI-powered models in the field. The product called VigiLens integrates AI technologies to provide real-time threat intelligence, vulnerability management, and incident response capabilities, highlighting the immense potential of AI in blockchain security.

In conclusion, the transparency of blockchain, when combined with AI and ML technologies, offers unprecedented opportunities for enhancing security. From transaction analysis to early detection of potential threats, AI is proving to be an indispensable tool in the world of blockchain security.

Going Further with Active Protection

Artificial Intelligence is proving to be a potent tool for enhancing blockchain security. It goes beyond basic transaction analysis and early detection of potential threats, finding applications in areas such as rugpull protection, user protection, validator behavior review, and bridge protection. Let’s delve into these areas one by one.

Artificial Intelligence is proving to be a potent tool for enhancing blockchain security.

Rugpull Protection

‘Rugpull’ is a term used in cryptocurrency to describe a malicious act where developers abandon a project and run away with investors’ funds. AI can be utilized to prevent such incidents through the analysis of transaction patterns within the protocol and the detection of unusual fund movements. Fraud detection machine learning models can be trained to identify patterns indicative of a potential rugpull, thereby alerting users and administrators in advance.

User Protection

In addition to protecting the protocol itself, AI can also be used to ensure the safety of users. One primary concern for users is phishing, where they might be tricked into revealing sensitive information. Anti-phishing measures can be implemented based on AI-powered analysis of transaction sources to detect and block such attempts.

An example of an initiative in this area is Wallet Guard. Their platform offers a layer of protection for users’ wallets against scams and frauds, illustrating the potential of AI in user protection.

Validator Misbehavior Review

In blockchain networks, validators play a crucial role in maintaining the integrity of the system. However, there may be instances where validators behave maliciously or carelessly, jeopardizing the network’s security. The Ronin network hack serves as a reminder of such incidents, where funds from a validator were stolen, and the breach went unnoticed for an extended period. AI can assist in reviewing validators’ actions, detect potential misbehavior, and raise alerts promptly.

Bridge Protection

Bridges, which facilitate transactions between blockchains, often accumulate substantial funds, making them attractive targets for hackers. 

A recent example is the Multichain hack. AI can play a vital role in protecting bridges through the analysis of signed messages and interaction patterns with the bridge, and early detection of requests for big amounts withdrawals.

As we continue to embrace the possibilities of AI, it’s clear that it can be a powerful ally in ensuring the integrity and security of blockchain networks. From transaction pattern analysis to real-time monitoring and early threat detection, AI technologies are significantly enhancing the resilience of blockchain systems against an ever-evolving threat landscape.

By harnessing AI’s potential, we can look forward to a future where blockchain security is more robust, responsive, and adaptable, providing a secure foundation for blockchain technology’s continued growth and evolution.

Thus, as the blockchain universe continues to expand and evolve, so too will the AI-powered technologies designed to protect it, offering promise for a secure future in the world of web3.

Blaize Security Knows How To Cover Your Security Needs

In summary, the first half of 2023 has been a remarkable journey for BlaizeSecurity in the realm of web3 security. Our AI and Blockchain-powered solutions have led to impressive achievements:

  • Comprehensive audits: BlaizeSecurity successfully completed 51 audits, including safeguarding our long-term partner Everstake with two audits.
  • Alchemy’s security list: We’re honored to be featured on Alchemy’s security list, a testament to our commitment to robust blockchain security.
  • DeFi Security Alliance: Membership in the DeFi Security Alliance strengthens our dedication to enhancing DeFi security.
  • Diverse ecosystems: BlaizeSecurity team expanded the expertise into ecosystems like Algorand, BTC (Stacks, Ordinals, BRC20), Cosmos, Polkadot, and Sui, driving innovation.
  • Industry participation: We actively participated in key industry events to enhance our knowledge and presence: Movecon online event, boosting our Move expertise, Incrypted conference, DeFi Security Summit.
  • Community Empowerment: Our #Web3SecurityTips initiative on Twitter shares valuable security insights with our community.
  • Strategic partnerships: Collaborations with QuillAudits and CyVers reinforce our position in securing digital assets.

We remain dedicated to your web3 project’s security. Stay tuned for more updates as we continue shaping the future of blockchain security. Your trust in BlaizeSecurity fuels our mission.

The Power of AI in Active Protection

Existing bots, such as “whale alerts” or scanners from Peckshield and other our colleges in security space have already demonstrated their effectiveness in alerting users to potential threats. However, integrating AI into the mix can significantly enhance the speed and accuracy of these alerts. 

Take, for instance, CyVers bot, an AI-powered solution that detects attacks as early as possible, providing an extra layer of security for the entire blockchain ecosystem. 

Blaize has recently partnered with CyVers – an AI-powered, recognized leader in proactive protocol protection, to deliver an end-to-end security solution unparalleled in the industry. Learn more about the details of the partnership here.

The fusion of AI and blockchain technology paves the way for a new era of active protection in the Web3 space. As hackers continually evolve their techniques, it is essential for security providers like Blaize to remain ahead by embracing modern tech. AI-driven audits, active protection measures, and early threat detection are powerful tools in maintaining the integrity and security of Web3 protocols, and they are vital to safeguarding the future of decentralized finance. 

Security experts worldwide continuously highlight the importance of the implementation of AI & ML techniques to enhance the level of security. Blaize Head of Security Pavlo Horbonos mentioned in his security-oriented blog:

If you can enhance web3 security with AI – just do it. We must be 10 steps ahead malicious actors – who also heard about AI.

Blaize Head of Security Pavlo Horbonos

Blaize, with our extensive experience in security and AI and our strategic partnership with security leaders like Cyvers, stands as a stronghold against such threats. We’re continually embracing and integrating innovative tech to ensure our clients are always ahead of the curve. With esteemed partners like Cyvers, Blaize is at the forefront of shaping this secure future. Together, we make AI and Blockchain a fortress of active protection.

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Pavlo Horbonos Image
Pavlo Horbonos
Head of Security
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