Preventing front running through privatized bids

In a traditional asset trading platform, front running is defined as the illegal practice of placing a trade based on advanced non-public knowledge of an upcoming trade which can impact prices. As shown in the example below, a broker can take advantage of a situation when he or she gets a large order by one of their clients. Since they know this order will impact the price of the asset, they place their own personal order ahead of their client’s order. Then, they place the client order, raising the stock price. Once this is done they will sell their own shares to profit off their clients order.

Another term used often is insider trading, which is based on a very similar practice of using information only they have access to in order to gain an unfair advantage over others.

Figure 1: Traditional front running

In the Web3 space, everything is transparent and, ironically, revealing too much information can also create these situations. An example of this is front running on a decentralized exchange (dex) that you may have already heard of. This type of a front running is possible through the combination of having total transparency in the blockchain along with how Ethereum (and many other blockchains) prioritize transactions in a node’s mempool.

In this particular example, an attacker (usually a bot) scans the mempool to see a particular scenario that they can take advantage of. Scanning the mempool, they look for an opportunity to insert in a bid at a lower price but higher gas than another large bid already in the mempool.

Figure 2.1: Front run attacks in a dex

Once their bid completes, they wait for the larger order to go through, raising the price of the asset. Then they place a sell order at a higher price than the buy order he placed ahead of the larger order, and pockets the difference. All this is happening in a blink of an eye, making it impossible for any normal person to be able to recognize they are being taken advantage of.

Figure 2.2: Front run attacks in a dex

But what if we could make the orders private? This prevents the attacker from being able to read the auction details in the mempool, and making the bot unable to identify a situation to take advantage of.

Figure 3: Privatized auction data on the blockchain

Through multiparty computation (MPC), details can be kept private while still computing the winner. In the situation of this dex, the results of the prices are not revealed until the bids are completed, ensuring that attackers cannot gain any advantageous information ahead of time.

Figure 4: Full support of various analysis using hidden data

The team in Partisia has already provided solutions to solve this issue in multiple scenarios. From governments to OTC trading platforms, they have been trusted to run high stakes auctions in different levels and through enabling this technology on a blockchain, we are giving everyone the power to solve the problem of ensuring integrity in the bidding process.

Figure 5: Partners whom we helped solve for integrity in auctions

For additional insights on this use case, we recommend viewing our Q&A session on this topic.

By creating a programming language that allows for developers to use MPC in a generic way, Partisia Blockchain Foundation has made the creation of applications that can harness the power of MPC for different use cases a possibility. Partisia has been at the forefront of providing private MPC solutions since 2008. And by layering this technology on top of an interoperable and scalable blockchain, Partisia Blockchain is now paving the way for anyone to create solutions that can balance privacy and transparency to build trust.

To learn more about different use cases or partner with us for solutions, please visit, check out our Medium articlesdevelopment documentations or email me at