Resources

People often ask me "How did you learn how to hack?" The answer: by reading. This page is a collection of the blog posts and other articles that I have accumulated over the years of my journey. Enjoy!

Different types of bot actions with frontrunning/backrunning with various markets:

• Sandwiching: Increase the price of the asset, let the trade happen, then trade back to make a profit.
• Sniping: Buy coins or assets as soon as they are listed.
• Backrunning: Arbitrage price inefficienies within an AMM. Usually the result of large trades.
• Just in time liquidity: Provide assets for a very short period of time for a single trade. Then, remove the assets after the trade to get the fees for providing liquidity. Only valuable for large trades.

This talk is about creating a backrunning bot that are mathematically optimal, which was prior to flashbots. The goal is to arbitrage (go from market A to market B to make a profit from the spread of the price) the differences between various pools. The author treats this as a graph theory problem where each token is a node and each AMM is a line to a different node. Using this, we can find a list of tokens to AMMs that could make a profit.

The first step is getting all of the data. These are pairs with tokens that have value (not meme coins) and the ratio (price) of these in the pool. From there, the author does an initial pass of these tokens from WETH to another token to see if the value went up or down in a breadth-first search pattern to see if the trading situation is good. If not, these tokens/pools are simply dropped.

Next, a depth first search is performed to find the best cycle possible. With the removal of meme coins and bad pools, this makes the search space tenable. To find the most optimal amount to trade on Uniswap is fairly easy. With Balancer, this is a much more complicated problem with the amount of tokens at place. So, this required using Newton's Method to find the profitability of various operations.

To execute this, the transaction is put on the network; but the work isn't done. Now, we need to check to see if there's any competition. If there's a collision in the tx.data, we need to see if our transaction will go through first or not. If it won't then will "fold" our previous transaction sent to minimize the loss, which is done by checking profitability at run time. We could also raise our gas price to see to try to get the transaction executed first.

Folds are important because only a single person can win the arbitrage. Additionally, there is some game theory here. The goal isn't to win a single opportunity; it's to win the most over time. So, sometimes, losing money by raising is more optimal than letting your opponent win. Over time, if you have a deeper pocket, you'll knock competitors out of the market. Obfuscating the code that is running to prevent people from doing this as well.

To make this more efficient, there are many things that you can do. First, caching is crucial. The paths can be cached and only updated on changes. This also goes for network requests for the pair information as well.

How is slippage dealt with on these calls? I'm not 100% sure. However, I've got some thoughts. Putting a transaction in the mempool will result in one of the pools being arbitraged or changed from a simple trade. If we can use the right amount of gas to ensure we're at the beginning of a block, this doesn't matter though. Additionally, there is a time of check vs. time of use (TOCTOU) issue, since the blockchain is always being updated. From my understanding, there's a gap (since transactions happen in blocks) so this isn't as much of a problem though.

At the end, the speaker gives advice on how to get into this: find a niche. JaredFromSubway will kill you if you try to start in his territory. So, finding a weird protocol on some sidechain with little competition works well for starting off. Then, you can work your way up to bigger and bigger things as you learn and build out infrastructure.

Overall, a good trip into the dark forest of MEV. It's fascinating seeing the optimization that goes into all of this.