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80% of trading volume comes from Rug funds: Behind the new high activity of Base chain, the shocking truth about Uniswap liquidity

80% of trading volume comes from Rug funds: Behind the new high activity of Base chain, the shocking truth about Uniswap liquidity

BlockBeatsBlockBeats2024/10/29 11:15
By:BlockBeats

A few lines of code, "Empty Hand Gloves for Free"

Base is becoming a shining star in the EVM field, but according to Dune data analyst jpn memelord, Uniswap's trading volume on the Base platform seems to be booming, but a large number of transactions are driven by repeatedly rugged capital pools. This seems to confirm some community views that there are many "big cuts" on Base. What is the real data? BlockBeats combined with jpn memelord's research to sort it out.


The false prosperity of Uniswap on Base


In early September, Uniswap tweeted that 98.9% of new trading pairs on Base were launched through the Uniswap protocol.



Data shows that the Base platform has launched more than 600,000 Uniswap v2 liquidity pools in the past few months, accounting for 98.9% of all newly created trading pairs on the platform, which is undoubtedly quite eye-catching. However, it is worth further exploring who created these trading pairs?


In fact, a considerable portion of the capital pools are deployed by a few addresses, and the top three addresses are actually associated, which means that a certain person or entity created 3.7% of the capital pools on Base, and some addresses are also associated.


Image source: Dune


In total, the addresses that created more than 500 pools contributed more than 127,000 pools, and more than 20% of all pools deployed on Base were created by only 87 independent addresses (or even fewer independent entities).


What are the actual conditions of these pools?


In fact, most of them are ordinary altcoins that are Rug within a few minutes and lack any real value. As the examples below show, these pools are not productive projects, but outright scams.



The strategy used by these mass pool operators is to disperse ETH to multiple wallets, then issue new tokens, buy through these backup wallets, and then quickly drain liquidity. This operation not only makes quick profits, but also artificially inflates trading volume indicators.


Each new Rug operation typically generates thousands of dollars in trading volume. These operations are carried out by dozens of addresses around the clock, and each pool lasts only 20-30 minutes, so a single address can launch more than 50 such projects per day.


In this way, each address can generate $250,000 in trading volume per day with only a small amount of initial funds.



"This is the equivalent of sticking a few $100 bills on a boomerang and throwing it 50 times. You haven't really generated hundreds of thousands of dollars in trading volume, you're just entertaining yourself." jpn memelord believes.


There may be many reasons why this phenomenon occurs frequently. On the one hand, it is to trick unsuspecting users into buying these tokens; on the other hand, it may be to profit from uncalibrated preemptive robots; in addition, it may be a strange act of plucking for possible (but unlikely) future Base airdrops.


The key question is how to effectively screen and filter these operations.


At first, jpn memelord thought that setting an upper limit on the number of pools created by each address could play a filtering role, so as to remove those junk addresses consisting of large pools of funds. However, he found that more than half of the pools were deployed by addresses that created fewer than 5 pools.


He speculated that many of the pools might have been created by Rug or Rug bots, which frequently change addresses to evade detection, and might even change addresses after deploying just one pool. Therefore, jpn memelord decided to dig deeper, trying to find traces of human factors in pool creation.


He tried focusing only on pools created by ENS users. This approach was more fruitful, with only 17,000 pools created by addresses that owned ENS, a number far lower than the total number of pools and likely effectively ruling out most pools created by bots.


Coincidentally, jpn memelord believes this screening process may have also revealed some influencers who repeatedly Rug Base tokens. However, this method still needs to be improved, and the existing filtering method may miss some real funding pools created by anonymous deployers, while including some vanity influencer scams or Rug projects.



jpn memelord started looking at pools with multiple liquidity addition events. Rug projects usually only do one liquidity injection and removal, while productive pools will have other liquidity providers injecting liquidity multiple times.


Only about 7,800 v2 pools have experienced multiple liquidity additions, and when the filter condition is increased to more than 2 liquidity additions, this number is halved again, leaving only about 3,500, which are productive pools, not just Rug projects.



These valuable pools only account for 1.2%-0.5% of the initial total, which means that after taking into account junk projects and scams, the actual data is exaggerated by about 99%, and this number is also very close to the number given by Uniswap at the beginning of the article.


jpn memelord believes that this behavior is not essentially the fault of Uniswap, because it is a permissionless protocol and anyone can create a pool for any asset, which is one of its design features. However, promoting indicators that are artificially inflated by worthless junk projects is something Uniswap has the ability to control.


Uniswap should filter its indicators. Whether it is 8,000 pools or 3,500, these pools that really generate some value are still impressive data. This filter should also apply to volume, as a significant portion of volume is actually generated by these Rug projects cycling between the same 5 ETH.


“Pools created” is an activity metric that is easily manipulated by robots for a permissionless protocol that costs only a few cents to operate. This type of metric should be carefully filtered and not simply promoted at face value. The pools that go beyond the Rug routine and are truly interactive are the ones worth paying attention to.


Rug is a disaster, and Uniswap’s real trading volume is inferior to Aerodrome


jpn memelord further explored whether these easily implemented Rug projects contributed significantly to trading volume.


At its peak, the pools with only one liquidity addition event contributed about $300 million in trading volume per month, which is a relatively small proportion. As of now, this figure for September is only about 30 million US dollars, which actually verifies that about 99% of the funds pools created by Uniswap on Base are low-value.



jpn memelord wanted to get a clearer picture of where this volume was really coming from. In previous analysis, he mentioned that while these low-cost Rug projects did contribute to volume, he suspected that more sophisticated operators would frequently switch addresses when launching new scams to evade detection.


So how can these operators be distinguished?


jpn memelord turned to AerodromeFi and its whitelisting process as a possible way to filter Uniswap's volume on Base. On Aerodrome, if a pool wants to receive incentives, its token must pass the whitelist review of the Aerodrome team, which helps to distinguish the volume of high-quality projects from other projects.


His analysis shows that a considerable portion of Uniswap's volume on Base actually comes from assets that are not whitelisted. Since the outbreak of projects on Base in March this year, this proportion is close to 50%.



Does Uniswap have an advantage on certain assets? What is driving these trading volumes?


jpn memelord extracted the trading volume data of individual pools of assets that were not whitelisted, and found a large number of meme coins. Some meme coins he had never heard of had a trading volume of 10 million US dollars in September alone.



After checking these pools one by one, he found that most of the tokens were in a "pulling the plug" situation. In fact, among the top 150 pools sorted by monthly trading volume, jpn memelord only found 4 without Rug.


These pools behave in roughly the same way: within hours of going live, they trade millions of dollars in volume, then quickly Rug, the tokens are sold off to zero, and the deployers make over 90 ETH in profit.


This operation is repeated over and over again.



So how do you identify these scams in the volume data? A systematic approach is needed to identify them.


When a token is completely Rug, trading stops. Therefore, these scams can be identified by setting a filter to check how much time has passed since the token was last traded.


The approach taken by jpn memelord is to apply a filter to filter tokens that have been traded in the last N days, which can distinguish "active" tokens from "inactive" tokens. Combined with the whitelist filter that has been used, Uniswap's trading volume can be divided into four categories:


· Active tokens in the whitelist: including high-quality tokens, stablecoins, and established meme coins.

· Inactive tokens in the whitelist: refers to tokens that have fallen sharply in recent months.

· Non-whitelist active tokens: include new tokens, both scam projects and real projects.

· Non-whitelist inactive tokens: usually serious Rug projects or assets that are gradually forgotten by the market.


So, what exactly is Uniswap's trading volume like?



First, these Rug tokens, which have traded $1.85 billion in September, have not traded in the past two days (~10% of the month), meaning these tokens make up 57% of Uniswap’s total volume on Base this month.


The situation is even more dire. Some of these “active” tokens have only Rug in the last 48 hours and are grouped in the pink section of the chart (non-whitelisted active), and if the “unplugged” volume remains almost constant, it can be expected that another ~6% of the monthly volume is also scam projects.


This segment accounts for 12% of the total volume this month, and last month this segment accounted for ~6% of the total volume, so it is likely that by the end of the month, this 6% will join the 57% after the activity filter identifies recent Rug projects. In other words, about 63% of Uniswap's volume on Base comes from the Rug project.


Whitelisted assets (high-quality token pairs, stablecoins, mature meme coins) account for only 30% of Uniswap's volume this month. The remaining 7% or so of monthly volume is the "advantage" that Uniswap has.


jpn memelord attached two sets of charts, one showing the unprocessed Uniswap volume (the data often used to compare these volumes), and the other removing Rug transactions from the Uniswap data. Aerodrome's volume dominance is far more powerful than one might think.



Interestingly, even after filtering out scam transactions, the overall trading volume on Base is still steadily increasing, and Aerodrome's market share is gradually expanding. By observing the increase in the percentage of trading volume, we can also see the significant increase brought by Aerodrome's launch of Slipstream (CL) in late April.



In-depth Rug details, a few lines of code "empty gloves white wolf"


As the market heats up, jpn memelord continues to pay attention to the continuous Rug operations on Base. This time, he found that these large numbers of abnormal operations may come from a certain individual or group.


Their operation began with the deployment of a token, strangely, with a non-standard 9 decimal places, and adding most of the liquidity to the Uniswap v2 pool. Subsequently, they opened transactions, gave up ownership of the contract, and destroyed the liquidity tokens. This series of operations looks like a compliant setup.



The wallet holding the most tokens on Basescan is a liquidity provider, and everything looks safe, attracting many people to flock to it.



The "security check" also seems to have passed the verification (LP has been destroyed, contract ownership has been abandoned, no honeypot, etc.). Despite this, @Token_Sniffer has already marked the scammer.



They then manipulated the trading volume through robots to lure unsuspecting users into taking the bait.


ETH was semi-randomly distributed to dozens of wallets controlled by the deployer, which simulated natural market demand and pushed up the chart trend through buy and sell operations.



Everything seemed normal until the deployer received a token transfer far exceeding the number shown in the "circulating supply", all the ETH in the pool was withdrawn to the deployer's account, and this seemingly safe meme coin was no longer in use.



Where did these tokens come from?


There is a constructor in the contract that intentionally uses integer underflow to assign the maximum uint256 amount of balance to a "hidden" wallet controlled by the deployer. Therefore, these tokens will not show up in the "max supply" or the list of holders on Basescan.



It is these few lines of code that make the chart look like this.


The ETH is recycled for the next operation, and the whole "show" starts over with a new token code, usually a name currently popular on Ethereum or Solana.


Has Base become a "minefield of death"?


jpn memelord continues to follow up on Uniswap's volume analysis on Base and found an active continuous Rug operator. In short, this person or group now accounts for 65%-80% of Uniswap's volume on Base every day.



The orange part represents the volume of the fund pool that has not traded in the past two days (i.e. Rug tokens/fund pools). In October alone, this part of the volume has reached nearly $5 billion, reaching the highest level since April.


To make matters worse, the proportion of this part of the volume in the total volume has increased in recent weeks, reaching 82% of the total volume on October 12. Most of the remaining volume comes from the token fund pools on the Aerodrome whitelist (including WETH, cbBTC, DEGEN, etc.).



This means that Base has become a minefield, and anyone trying to find new tokens there has a high probability of encountering these Rug projects.

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Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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