Web3 has been expanding rapidly in recent years, boasting millions of users worldwide, but have you wondered how much of that growth is real? The truth is that a big chunk of Web3 activity is generated by bots and fake users. To ensure the next iteration of the internet grows organically, the sector needs to reduce the negative effects of bots. The scale of the on-chain bot problem When I dug deeper, I was blown away by the scale of bot activity in Web3. They’re everywhere, from driving metrics on decentralized finance (DeFi) protocols to inflating non-fungible token (NFT) and GameFi figures. In the NFT sector, CryptoSlam data shows that 42.52% of all trading activity on Ethereum relates to wash trading, a manipulative strategy where the same person or group buys and sells NFTs in a loop to inflate volume numbers. This represents over $34 billion of fake volume. 42.52% 42.52% In the broader Web3 space, a 2022 study from bot prevention service Jigger found that 40% of all active users in Web3 games were actually automated bots or fake users. found that 40% found that 40% And what about this? Over the three months to November 2025, bots were behind 80% of tracked stablecoin transactions, according to data from fintech giant Visa and blockchain data firm Allium. We’re speaking about $13.2 trillion of reported trading volume, of which more than $13 trillion has been non-human. data data Why projects inflate their numbers with bots The bot plague has several explanations. To begin with, one of the key reasons behind fake data is the need to attract users and investors. By appearing more successful than they really are, many Web3 projects hope to boost investor confidence. In crypto, metrics are often the main fundamental factor driving prices, and they need to look good to fuel the FOMO effect. For early-stage crypto projects, stimulating activity with artificially inflated metrics may be a way to secure venture capital or private funds and find a backdoor to exchange listings. How on-chain bots distort Web3 growth narratives Needless to say, inflated data misleads everyone, including investors, advertisers, policymakers, and end users like you and me. For example, when you’re ready to gain exposure to an early-stage project with good metrics that no one knows about yet, how disappointed would you be to find out it was all just vanity metrics? This happens very often in crypto. Another reason behind bot activity is the hunt for profits. Many users rely on MEV bots, which manipulate blockchain transaction orders inside a block, trading bots, and other automation tools to scan the crypto market and streamline the trading experience. Sectors most affected Web3 bots have become the norm, but certain sectors are more affected than others. Let’s briefly explore where to stay sharp: DeFi wash trading Wash trading is a big problem in DeFi. As discussed earlier, this practice is used to create a false impression of high trading volume. As a result, users would buy a token or deposit funds more confidently, eventually leading to an increase in the protocol’s total value locked (TVL). In 2023, a Glassnode report showed that 70% of trading volume on Uniswap, the largest decentralized exchange (DEX), came from bots alone, mainly from sandwich bots and arbitrage bots. Glassnode report Glassnode report While Uniswap is a multi-chain protocol focusing on the Ethereum ecosystem, Solana is another chain dealing with high bot activity. A Cardano Stake Pool Operator, known as Dave, said on X that a bot executed 11 million transactions in a month on Solana with a failure rate of 99.95%, distorting the reported volumes. said on X said on X NFT marketplace bots The NFT sector is affected by wash trading as well, probably even worse than DEXs and other DeFi protocols. We mentioned that over 40% of all NFT trades on Ethereum were detected as wash trading. This is by far the highest proportion among all chains, with Polygon and Base seeing 20% of their volumes deemed fake. GameFi inflated daily active wallets Blockchain games, including the GameFi sector with its play-to-earn (P2E) model and other incentives, account for the largest share of dApp activity, according to DappRadar. In fact, games expanded their share in Q3 2025 compared to the previous quarter, highlighting their dominant position. DappRadar DappRadar The bad news is that a significant portion of this activity is driven by Web3 on-chain bots. They affect the game economies, marketing, and the gameplay itself. The Jigger report analyzed more than 60 Web3 games and found over 200,000 bots. Some top games on the BNB Chain had bots making up 70% of their monthly active users. 70% 70% How bots are detected in Web3 Many bots benefit from AI, but the technology is also used to detect and prevent the bad influence of bots and fake user agents. Some of the basic methods used to identify bot activity involve the on-chain and off-chain analysis of user behavior. Specialized tools can check IP addresses against existing malicious lists or monitor for anomalies in trading volume and activity. Thanks to AI, these tools can detect complex patterns in large datasets that would otherwise go unnoticed by the human eye. AnChain.AI, Nansen, Allium, and Chainalysis are some of the reputable blockchain security firms employing AI and machine learning (ML) to filter out wash trading, scams, and bot-driven metrics. The consequences of ignoring the problem Turning a blind eye to fake users and bot-generated metrics erodes the very foundation of Web3. The sector relies on blockchain to ensure decentralization, transparency, inclusiveness, data control, and a more democratic financial system. If left unchecked, the bot problem could lead to tighter regulatory scrutiny and a slower adoption. However, it’s not fair to make Web3 the scapegoat – bots are a problem in Web2 as well. Cybersecurity firm Imperva found that automated and AI-powered bots accounted for more than half of all web traffic in 2024, especially due to advanced AI tools like ChatGPT and Gemini. What’s concerning, traffic from “bad bots” rose to the highest level on record. found found “With generative AI simplifying bot development, automated threats are evolving rapidly – becoming more sophisticated, evasive, and widespread, fueling the growth of both simple and advanced bad bots,” the report said. With generative AI simplifying bot development, automated threats are evolving rapidly – becoming more sophisticated, evasive, and widespread, fueling the growth of both simple and advanced bad bots,” Can Web3 fix its bot problem? I don’t think we can get rid of bots entirely, but we can definitely reduce their negative impact. With smarter on-chain analysis, advanced identity systems for certain use cases, bot-resistant incentive models, and AI-powered tools, we can make Web3 a better environment for all stakeholders. Many Web3 sectors are already improving. For example, MarketingFi is a new trend where mass rewards for small actions (a magnet for bots) are replaced with generous bonuses for users who actually engage and bring quality. What we should do is implement entry barriers for bots and improve detection methods, and AI is the key here, and it should outsmart bad actors exploiting the technology. Conclusion If Web3 aims to onboard the next 100 million real users, it needs to clean house. It’s true that gaining visibility and investor attention in crypto is difficult, but inflated numbers should not be the solution. They may win attention in the short term and for certain emerging projects, but the lasting bad effect is more serious: these manipulative schemes erode trust and postpone innovation. Solving the bot crisis isn’t just a technical challenge - it’s the next major task to resolve in order to unlock mass adoption.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

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When Wallets Lie - Measuring Real Users in a Bot-Driven Web3

When Wallets Lie - Measuring Real Users in a Bot-Driven Web3

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