What is a mempool?
MemPool (short for memory pool) is a temporary storage for transactions awaiting confirmation on the blockchain. This is where user-initiated transactions are held until miners and validators include them in the blockchain, provided they are valid.
In systems like Bitcoin, transactions are queued, with those offering higher fees typically confirmed first. During periods of high network congestion, confirmation times can significantly exceed the average block discovery time due to the large number of pending transactions.
In short, the mempool plays a crucial role in managing transaction flow, directly impacting confirmation speed and the economic incentives of network participants.
The MEV and censorship problem
MEV (Maximal Extractable Value, “Maximal Extractable Value”) is additional profit generated when participants increase their earnings by influencing the order of transactions during block creation. MEV is sometimes referred to as a specific strategy for extracting additional profit. Those who analyze mempool data to identify potentially profitable operations are often called “searchers.” Interestingly, they are not the only beneficiaries of this strategy, as transaction validators can ultimately collect higher fees as well.
MEV implementation can vary. The simplest way to explain the general logic of profit extraction through mempool analysis and transaction ordering is via a hypothetical frontrunning method involving an arbitrage trade. A bot scanner, analyzing data on unconfirmed transactions in the mempool, could theoretically detect an arbitrage trade being executed by another user and copy it by offering a higher gas fee. In this case, validators would prioritize the more profitable transaction from the frontrunner, processing it first, which may alter the asset price in the original arbitrage trade. As a result, the original trade would no longer be profitable—the frontrunner simply outpaces the honest user.
Another example of front-running is purchasing an asset ahead of time, such as before the launch of a new token. Backrunning is sometimes distinguished as a separate strategy—placing a transaction immediately after a target transaction from a regular user within the same block, exploiting a short-term window of opportunity.
Another method is called a sandwich attack, where the attacker places two transactions around the victim’s transaction—one before (front-running) and one after (back-running). As a result, the search bot buys the asset before the victim’s transaction, shifting the price, and then sells immediately afterward. This type of MEV is considered unethical because it degrades execution for non-MEV users.
It is also important to consider the hypothetical possibility of censoring specific transactions during their open processing. In such a scenario, encryption provides a solution to this issue.
In other words, there are many scenarios where analyzing open mempool data harms many participants. But what does an alternative approach to storing unprocessed transactions look like?
Encrypted mempool
An encrypted mempool (or encrypted mempool) is an alternative implementation of a transaction pool in which the contents of each transaction are encrypted and remain inaccessible to observers until the order of transactions in a block is finalized. In simpler terms, instead of sending plaintext containing the recipient’s address and amount into the network, the user sends ciphertext—a set of data that cannot be read in the usual open sense. Miners can see that a transaction exists and may even verify its basic validity, but they cannot see its specific contents.
This is why this approach changes the very logic of MEV handling. A malicious actor simply cannot see the contents of the transaction and therefore cannot effectively extract profit by analyzing public data. By the time the information is revealed, the order is already finalized and manipulation is no longer possible. In theory, this creates conditions for a fairer and more predictable market.
Conceptually, an encrypted mempool is a fairly solid solution. The technology itself complicates the security model of the transaction processing process. An encrypted mempool alters the “lifecycle” of a transaction, as the protocol must determine exactly when and how the decryption of an encrypted transaction is permitted.
Data processing procedure
In a system with an encrypted mempool, transaction data is encrypted locally by the user, who then broadcasts the ciphertext to the network. Validators subsequently process and order the transactions without accessing their contents. At the protocol-specified stage, once the transaction order is finalized, the encrypted data is decrypted. Threshold encryption is one possible mechanism for implementing this process.
It’s important to note that an encrypted mempool is a complex system that must account for many aspects of network operation: the optimal timing for decrypting data, strict adherence to transaction conditions, protection against malicious validators, and more. Therefore, specific implementations of the technology may vary.
Problems with the encrypted mempool
As we can see, this type of solution adds additional network overhead, as users must encrypt their data, and the system must decrypt it after processing. This increases computational load and sometimes transaction size. Notably, transaction fees are often tied to the latter metric, meaning an encrypted mempool can be more expensive to use.
From an economic perspective, the system cannot be called perfectly efficient. Although transaction amounts, processing times, costs, and other data may be misused by unscrupulous researchers, they nonetheless lead to rational monetary circulation from an economic standpoint—wherever profit opportunities arise, participants immediately extract value through MEV, much like cross-exchange arbitrage.
In simpler terms, one could interpret this as: the market system, through data transparency, enables fairly efficient resource allocation—even if achieved through unethical practices. In contrast, when data is encrypted, greater uncertainty arises within the system—for example, regarding fee structures. For this reason, the technology is often described as a solution that is not universal and, incidentally, does not fully eliminate any theoretically possible MEV. That’s why, alongside encrypted mempools, you sometimes encounter approaches such as randomized ordering. However, these approaches can sometimes complement each other in certain scenarios.
Examples of use
On May 12, 2026, representatives of the Aptos project announced an update integrating an encrypted mempool. The innovation, implemented through batch threshold encryption technology, is designed by developers to prevent attacks such as front-running.
The blockchain platform Secret Network, whose main feature is encrypted smart contracts and data privacy support, also uses encrypted mempools. Developers explicitly state that they have achieved frontrunning resistance.
The Oasis Network project uses encrypted transaction and private mempool technology within its confidential execution environments (ParaTimes), achieved through hardware-based TEE technology (Trusted Execution Environments).
Withdraw
Encrypted mempools are a response to the fundamental transparency issue of blockchains: what makes a network open and verifiable also creates opportunities for MEV extraction from users. Encrypting transactions until final ordering theoretically eliminates this problem, making the process fairer and more predictable. However, it cannot be definitively stated that an encrypted mempool is a cure-all. The technology itself is full of trade-offs. The field is actively evolving, but widespread adoption is still far off. The question is not whether such technology is possible in principle, but whether it can be integrated into existing ecosystems without compromising their stability, performance, and so on.