Full Report
Maximal Extractable Value (MEV) is the value that can be extracted by manipulating the transaction sequencing. By adding, removing and/or reordering transactions within a block, it's possible to profit from it. This article is a perspective on Solana MEV over the last 4 years. The first big change in the Solana MEV space was the introduction of the JITO-Solana client. By allowing block-searchers to choose what transactions go into a block in a democratic way with a bidding process, the validators and searchers are able to profit from it. The JITO-Solana client makes up 92% of clients now. In March of 2024, Jito decided to shut this down because it was hurting average users. Even though JITO is now gone, there are other similar products to it. Much of Solana sandwiching attacks originate from a private mempool called DeezNode. In May of 2024, the scheduler algorithm was made more stable, which prevented leader spamming attacks too. What type of MEV is profitable? The classic one is arbitrage. You can buy something at $1 and then sell it for $3; you make $2. By changing the cost of things with sandwiching, you can arbitrage users to make large profits. Another form of MEV is performing liquidations on lending protocols. An insight they show is the amount of reverted transactions on Solana. Since a single user can only hit a MEV opportunity, all others will fail. This bot spam counted for 75% of all non-vote transactions in the network, leading to major issues in throughput. The new scheduler has majorly improved on this problem, though. Jito attempts to keep track of MEV in the Solana network through their mempool and elsewhere. According to the report, 50% of sandwich attacks come from a program owned by DeezNode. On average, they make 51K transactions in a single day at 2200 SOL per day. Jito shutting down their mempool was nice. However, unless there's a built in way to stop this, some actor will decide to do this. How do we stop MEV then? A scary way is validator whitelists. Jupiter, a retail trading platform, introduced dynamic slippage to optimize settings in real-time. Another one that is common by AMM's is to route transactions to only go through the Jito block engine without sandwiching. RFQ (request for quotation) is an off-chain pricing mechanism where market makers bit for prices, with only the final quote being used on chain. JupiterZ and Kamino swap do similar things but follow this underlying principle. Along the same lines are Sandwich-resistant AMMs. No swaps are executed at a price more favorable than the pool's price at the start of a slow window. Because of the long periods of time that prices stay, sandwiching is impossible. Similar to SR AMMs is Conditional Liquidity, which depends on a new user called "Segmenters" to evaluate the incoming toxicity of the order flow. By adjusting the spreads based on this, we can prevent the profitability of the MEV folks. The spread is paid back as compensation for the Segmenters role. Paladin-Solana aims to be a trusted priority port that can be used but punishes folks who MEV on it. Overall, a good article that explains the wild world of MEV in the Solana ecosystem. Maybe one day we'll get rid of it.
Analysis Summary
# Research: Solana MEV Report: Trends, Insights, and Challenges
## Metadata
- **Authors:** Lostin (with reviews by Lucas Bruder, Max Resnick, Eugene Chen, Mert Mumtaz, and others)
- **Institution:** Helius
- **Publication:** Helius Blog / Research
- **Date:** January 15, 2025
## Abstract
This report provides a longitudinal analysis of the Maximal Extractable Value (MEV) landscape on the Solana blockchain over the last four years. It examines the shift from the dominance of Jito-Solana clients to the rise of private mempools and "dark" MEV following the suspension of Jito’s public mempool. The research quantifies the economic impact of arbitrage and sandwiching attacks, identifies key actors like DeezNode, and evaluates emerging technical countermeasures such as Sandwich-Resistant AMMs and Conditional Liquidity.
## Research Objective
The research aims to map the evolution of MEV on Solana, quantify current profitability across different strategies (arbitrage vs. sandwiching), identify the infrastructure facilitating these attacks, and propose architectural solutions to mitigate the "negative sum" aspects of MEV that harm retail users.
## Methodology
### Approach
The study employs a mix of on-chain data analysis, historical narrative tracking, and technical evaluation of network upgrades (e.g., the scheduler stability improvements of May 2024).
### Dataset/Environment
- **Timeframe:** Approximately four years of Solana history, with deep dives into 2024 and early 2025 data.
- **Scope:** 3 billion+ Jito bundles, successfully identified arbitrage transactions, and targeted analysis of specific sandwiching bots (e.g., DeezNode).
### Tools & Technologies
- **Jito-Solana Client:** Used for bundle data and arbitrage detection algorithms.
- **Helius RPC & Indexing:** For real-time and historical transaction analysis.
- **Sandwiched.me:** A visualization tool for tracking active sandwich attacks.
## Key Findings
### Primary Results
1. **Dominance of Jito:** The Jito-Solana client comprises 92% of the network, though Jito’s public mempool was shuttered in March 2024 to curb toxic MEV.
2. **Centralization of Toxic MEV:** Since Jito’s mempool closure, sandwiching has migrated to private mempools. 50% of all sandwich attacks are attributed to a single program owned by **DeezNode**.
3. **Spam as a Throughput Bottleneck:** Failed MEV attempts (reverted transactions) previously accounted for 75% of non-vote traffic, though recent scheduler improvements have stabilized the network.
4. **Economic Scale:** Arbitrage generated $142.8M in profits over the past year. A single sandwiching bot (vpeNAL...) generated ~65,880 SOL ($13.43M) in just 30 days.
### Supporting Evidence
- **Statistic:** DeezNode’s validator stake grew from 307k to 802k SOL in less than a month, highlighting how MEV profits scale influence via stake delegation.
- **Empirical Data:** Jito bundles generated 3.75 million SOL in tips over the last year, showing a massive upward trend in network valuation.
### Novel Contributions
- Identification of the "DeezNode" private mempool as a primary source of network friction.
- Evaluation of **Conditional Liquidity** and **Segmenters** as a social/technical hybrid defense against toxic order flow.
## Technical Details
The report highlights the **Solana Scheduler** upgrade in May 2024, which transitioned the network from a state where leader spamming was the primary extraction method to one where priority fees and bundles are more structured. It also details **Sandwich-Resistant AMMs (SR-AMMs)**, which utilize "slow windows"—ensuring no swap executes at a price better than the pool's price at the start of the slot, effectively making sub-slot price manipulation unprofitable.
## Practical Implications
### For Security Practitioners
- **Monitor Private Mempools:** Security audits must now consider out-of-protocol transaction flows (like DeezNode) rather than just on-chain transparency.
### For Defenders
- **Dynamic Slippage:** Retail platforms (e.g., Jupiter) should implement real-time slippage optimization to reduce the "bribe" space for sandwich bots.
- **Alternative Routing:** Developers should route trades through Jito's block engine or use Request for Quotation (RFQ) models to bypass the public/private mempool competition.
### For Researchers
- **Validator Centralization:** Investigate the feedback loop where MEV profits are used to buy more stake (Marinade’s SAM marketplace is a key area of concern here).
## Limitations
- **Data Opacity:** Since the closure of Jito’s mempool, "dark" MEV occurring in private mempools is harder to quantify with 100% precision.
- **Adoption Barriers:** Many proposed solutions (like MCL) are years away from full-scale production readiness.
## Comparison to Prior Work
Unlike Ethereum's Flashbots model (MEV-Boost), which is highly transparent, this research shows Solana's MEV is bifurcating into a high-transparency arbitrage sector (Jito) and a low-transparency "dark" sector (Private mempools/DeezNode).
## Real-world Applications
- **JupiterZ/Kamino Swap:** Implementing RFQ mechanisms to protect users.
- **Paladin-Solana:** A "trusted" priority port that uses social slashing to punish validators who engage in harmful MEV.
## Future Work
- **Asynchronous Execution (AE):** Researching how construction of blocks without immediate execution affects a searcher's ability to calculate profitable sandwiches in real-time.
- **MEV-Aware AMMs:** Further development of "Segmenters" to adjust spreads based on the "toxicity" of incoming order flow.
## References
- *Helius Blog: MEV an Introduction*
- *Chorus One: Arbitrage as a Convex Optimization Problem*
- *Multicoin Capital: Value Capture Distribution of MEV*