Memecoins Gone Wild: When Compliance Gets Weird

Late last year, pump.fun, a wildly popular platform for launching tokens on Solana, shut down its live streaming functionality after a deluge of behavior that violated its safety and integrity standards. People filmed themselves shooting guns, smoking crack, and threatening suicide -- all in an effort to gather attention and increase the value of their coins. Just another day on the Internet, but what does any of this have to do with compliance?

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Pump.fun has attracted more than 14 million wallets and generated over 6 million tokens, known as memecoins because of their humorous nature, fleeting value, and reliance on speculative hype. It also became synonymous with rug pulls, scams where developers suddenly dump their coin and leave the investors holding the bag. The legality of pump.fun aside, financial institutions and exchanges will want to avoid any association with byproducts of crypto's numerous gray areas. Traditional compliance tools fall woefully short. Here’s why—and how we fix it.

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Compliance in the Age of Memecoins

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Modern compliance is deeply rooted in the nation state's pursuit of making societies more "readable" for purposes of control, taxation, governance, and resource allocation. Starting with 19th century regulations aimed at banknote issuance all the way to anti-money laundering (AML) legislation of the 1970s and modern Environmental, Social, and Governance (ESG) frameworks, compliance has been about making financial activities, corporate behavior, and market dynamics transparent to regulators, stakeholders, and the public.

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Traditional Web3 compliance inherits this emphasis on legibility and relies on static databases of bad actors that clients can reference to filter transactions. This approach involves a time-intensive process of data collection and address labeling that relies on human intervention and decision making, which takes weeks to update with new information and often misses bad actors altogether. More importantly, this cadastral survey approach to Web3 compliance is a fundamentally poor match for blockchains.

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Why Current Approaches Don't Work in Web3
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• Dynamic and Decentralized Nature of Web3 -- transactions, wallet addresses, and participants are constantly changing and there is no centralized authority or permanent identity tied to wallets.
• Pseudonymity and Obfuscation -- a wallet flagged in a static database may simply be abandoned in favor of a new one and pseudonymous identities require minimal effort.
• Lack of Context in Static Lists -- static databases often classify addresses as either "bad" or "good," which oversimplifies the complex realities of Web3 transactions. A new address may inherit taint due to proximity in transaction chains, creating false positives.
• Lack of Behavior Analysis  -- these lists don't account for nuanced behaviors or intent behind transactions, which limits their ability to differentiate between legitimate and malicious actors.
• Speed and Real-Time Challenges -- static databases introduce delays in compliance processes and bad actors can exploit time gaps between database updates.
• Cross-Chain Complexity -- static databases are not good at tracking activities effectively across chains or adapt to the interoperability inherent in Web3 and are susceptible to evasion via bridges
• Adversarial Innovation -- static databases react to identified bad actors post-incident rather than proactively analyzing evolving threats, which results in a game of "whack-a-mole," where bad actors stay one step ahead.

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In the world where 10,000 wallets can be created with a few lines of code in under a minute and a life cycle of a pump-and-dump memecoin spans mere hours, traditional compliance leaves financial institutions and exchanges vulnerable. This risk gap between crypto and traditional finance needs to be addressed for Web3 to achieve mainstream adoption. 

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Toward Web3-Native Compliance

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What the industry needs is real time compliance that continuously monitors activity at the block level and instantly updates address reputation. This Web3-native approach also needs to take into account direct as well as indirect (multi-hop) exposure to illicit activity across multiple chains. The high-accuracy alerts generated by that kind monitoring can then be connected to automated actions to create a truly proactive compliance stack.

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We built Hypernative to be that solution. The system tracks funds across bridges and value transfers across more than 50 blockchains using both onchain and offchain data sources. Our battle-tested, sophisticated machine learning models, heuristics, simulations, and graph-based detections can identify over 300 risk types, helping secure more than $100 billion of customer funds.

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This is a fundamentally different approach that focuses on how bad guys behave by identifying patterns, instead of trying to keep track of all of their wallet addresses. Some giveaway signs of malicious intent that cannot be tracked by a database and are easily detected by Hypernative are:

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• funds funneled through multiple wallets to obfuscate their origins
• funds moving across multiple networks to use cross-chain bridges as barriers to detection
• a dormant account suddenly receiving an influx of funds
• a wallet collecting funds from many addresses
• one consolidated account splitting up into many and reforming again

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Pump.fun may be a flash in a pan, but it is part of the broader phenomenon that technology observer Venkatesh Rao termed as the Great Weirding. This transitional and chaotic era, marked by a breakdown of established systems and emergence of chaos agents like memecoins, requires us to abandon traditional practices in favor of adaptive approaches.

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‍Reach out to learn how Hypernative can future-proof your compliance, tune into Hypernative’s blog and our social channels to keep up with the latest on cybersecurity in Web3.Secure everything you build, run and own in Web3 with Hypernative.

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