Governance Extractable Value (GEV)

• Governance Extractable Value (GEV) is defined as the incremental profit gained by privileged blockchain actors through manipulation of transaction ordering and block composition.
• GEV involves methods such as transaction reordering, injection, and exclusion, allowing miners and validators to capture value beyond standard protocol rewards.
• Mitigation strategies like randomized ordering, accountable mempools, and commit-reveal schemes are designed to reduce the systemic risks and centralization effects linked to GEV.

Governance Extractable Value (GEV) is a specialized notion within the literature of transaction sequencing and MEV (Maximal Extractable Value), designating the component of MEV that can be attributed to agents exercising privileged control over block construction—typically, those responsible for protocol-level transaction ordering or inclusion—under the rules of a blockchain protocol. GEV arises whenever those governance actors (miners, validators, or designated sequencers) can manipulate transaction ordering, block composition, or execution timing to elicit incremental profit, beyond what would be possible under a credibly neutral protocol. The study of GEV is critical for understanding the economic and incentive-theoretic foundations of transaction inclusion, system fairness, and the viability of MEV mitigation mechanisms.

1. Formal Definition and Conceptual Scope

GEV generalizes the more operational notion of MEV by focusing explicitly on the value extractable through governance prerogatives—those transaction manipulation opportunities that can only be exercised by actors authorized to determine block contents and order. Daian et al.'s formalization of MEV is preserved but emphasizes the set of orderings and inclusions accessible to "governance-authorized" entities:

$$\mathrm{GEV}(B) = \max_{\pi \in \mathcal{O}_G}\; \mathrm{Profit}(\pi(B)) - \mathrm{Profit}(\pi_0(B))$$

where $\mathcal{O}_G$ is the set of orderings/inclusions permitted to actors with governance status, and $\pi_0$ is the protocol-mandated reference sequence (e.g., time-of-arrival or fair random order). In the context of Ethereum, for instance, this includes all orderings miners or block proposers can choose when constructing a block from the visible mempool (Sarkar, 2023, Piet et al., 2022, Nasrulin et al., 2023). Governance authority typically arises from protocol or consensus roles but may also attach to sequencer collectives or committee-based ordering mechanisms (Alipanahloo et al., 2024, Yang et al., 2022).

GEV is distinguished from "searcher MEV" (profit extractable by adversarial users that submit bundles/bids) by the requirement for internal protocol prerogative—searchers are forced to compete for the residual value after governance actors have exercised their sequencing advantage.

2. Transaction Manipulation Primitives Associated with GEV

GEV encompasses several manipulation primitives, all deeply tied to governance-level powers over block construction (Nasrulin et al., 2023, Piet et al., 2022):

• Reordering: The governance actor may permute the order of transactions, enabling front-running, back-running, and sandwiching. For instance, a validator can place its own transaction to front-run a large DEX trade and subsequently back-run for arbitrage (Sarkar, 2023, Kulkarni et al., 2022).
• Injection: The actor can insert privileged transactions into the block, often with access to mempool or bundle observation unavailable to ordinary users.
• Exclusion (Censorship): The governance actor can omit targeted transactions (e.g., competing MEV searcher bundles) to assure the profitability of its own inserted transactions or bundles.
• Time-Bandit Reorgs: In protocols with probabilistic finality (e.g., Proof-of-Work chains), block proposers may attempt chain reorganizations—re-mining prior blocks to capture MEV in high-value intervals (Piet et al., 2022, Bar-Zur et al., 26 Nov 2025).

These manipulation classes are only available to governance actors due to their protocol-bestowed discretion over block assembly.

3. Mathematical Frameworks for GEV Quantification

GEV is rigorously quantified using group-theoretic, optimization, and game-theoretic constructs. The "cost of MEV" framework (Angeris et al., 2023) measures the gap between maximal and average protocol profit as:

$$C(f,x) = \max_{\pi\in S} f(\pi(x)) - \mathbb{E}_{\pi}[f(\pi(x))]$$

where $f$ captures the governance actor's profit from a given transaction ordering.

In practical systems, GEV is measured by constructing actual transfer graphs, classifying cycles representing miner-induced arbitrage (e.g., via sandwiching or cross-DEX trades), and empirically computing their value from the transaction execution trace (Piet et al., 2022). Advanced models including Markov Decision Processes account for the stochasticity of block arrival, protocol constraints, and the random emergence of high-profit ("whale") MEV opportunities (Bar-Zur et al., 26 Nov 2025).

4. Incentive Analysis and Systemic Risks

A central insight is that GEV is not a static feature—it dynamically shapes participant incentives, especially when MEV/GEV-derived profit dominates ordinary block rewards. Key impacts include:

• Decentralization Erosion: High GEV concentration incentivizes collusion or vertical integration among governance actors (e.g., builders, relays, proposers), evident in the centralization of Flashbots and MEV-Boost relays (Wahrstätter et al., 2023, Weintraub et al., 2022).
• Security Threshold Reduction: In chains with variable block rewards due to GEV, the threshold of computational or staking power needed to launch profitable selfish-mining attacks can drop precipitously—well below classical 25% (Bitcoin) boundaries (Bar-Zur et al., 26 Nov 2025). Table 1 in (Bar-Zur et al., 26 Nov 2025) demonstrates this with security thresholds falling to 0% under sufficient GEV but being restored in robust protocols like MAD-DAG.
• Consensus Stability: Periods of elevated GEV (e.g., during DeFi liquidations or market crises) induce block withholding, reorg racing, and heightened fork risk, threatening finality and liveness (Wahrstätter et al., 2023, Li et al., 2023).
• Protocol Fairness: GEV extraction imposes an implicit "tax" on ordinary users, as unpredictable transaction inclusion and slippage erode confidence in smart contract platforms (Sarkar, 2023).

5. Mitigation Architectures and Design Patterns

Numerous techniques aim to neutralize, redistribute, or detect GEV, with leading approaches including:

• Randomized Transaction Ordering: Approaches such as FairFlow interpose VRF-based randomization after blockspace auctions to enforce ex post fairness, ensuring that the expected MEV is distributed across all transaction orderings and instantly limiting predictable GEV (Sarkar, 2023). The expected MEV bound is:

$$\mathbb{E}[\mathrm{MEV}] \leq \frac{1}{|\mathcal W|} \sum_{i<j} \Delta_{ij}$$

• Accountable Mempools: Protocols such as LØ enforce append-only transaction logs, verifiable inclusion order, and cryptographic commitments, enabling detection and public proof of any block-level reordering, censorship, or injection (Nasrulin et al., 2023).
• Two-Phase Commit/Reveal: Mechanisms like CoMMA replace direct mempool submission with a commit phase and blind preemption tokens. Since transaction contents are hidden until reveal, GEV is precluded for all intents and purposes (Churiwala et al., 2022).
• Batch Clearing and Sequencing Fairness: Batch mechanisms for AMMs process entire blocks atomically, providing arbitrage resilience and neutralizing block builder GEV (Chan et al., 2024).
• Game-Theoretic and Auction-Based Mechanisms: Systems that interpose sealed-bid auctions or VCG pricing for blockspace allocation ensure that GEV is redistributed in proportion to economic intent, rather than governance privilege (Sarkar, 2023, Mazorra et al., 2022).

These designs rely fundamentally on reducing or obfuscating the block assembler's discretionary power.

6. Empirical Evidence on GEV Prevalence and Effects

Empirical analyses consistently demonstrate that governance actors capture the majority of extractable value in representative blockchains:

• In a high-resolution study of Ethereum, miners collected 65.9\% of observed MEV (≈1,422 ETH in 12 days), dominating bots that employed bundled private relay submissions (Piet et al., 2022).
• Flashbots and similar private MEV pools, governed by miners or their delegates, are responsible for over 80% of all MEV extraction, with the remaining 13.2% traced to smaller private pools, and a negligible ~5% to the public mempool (Weintraub et al., 2022, Wahrstätter et al., 2023).
• The flashpoint mechanism for governance-enabled extraction is the centralization of ordering mechanisms—top two miners or builders consistently account for >90% of high-value MEV blocks in Ethereum epochs (Weintraub et al., 2022, Wahrstätter et al., 2023).

The prevalence of time-bandit blocks—where MEV exceeds 4x the block reward—creates persistent incentive for chain reorgs; in one observed period, four such blocks were identified, confirming the realism of this threat (Piet et al., 2022).

7. Future Directions and Open Challenges

While cryptographic and auction-based GEV mitigations have achieved partial mainnet deployment (e.g., FairFlow, LØ, commit-reveal protocols), several foundational challenges persist:

• Collusion and Subtle Manipulation: Techniques such as open VRF transcripts and on-chain slashing are proposed to deter collusion among protocol governance participants, but effective collusion detection is nontrivial at scale (Sarkar, 2023).
• Cross-Chain GEV: Extending GEV mitigation to multi-domain systems (e.g., Polkadot, Cosmos) raises the complexity of randomization and sequencing guarantees (Sarkar, 2023).
• Economic Incentive Engineering: Designing VCG- or threshold-based redistributive mechanisms that are robust to all deviations by block producers remains an open field (Sarkar, 2023).
• Formal Verification and Machine-Checked Security: Mechanized formalization of GEV upper bounds, as exemplified by recent Lean-based methodology, may become the standard for protocol guarantees (Bartoletti et al., 16 Oct 2025).
• Protocol Layer Upgrades: The transition from off-chain MEV markets to protocol-embedded, permissionless, and parameterized sequencing rules, as called for by practitioners and theorists, presents significant technical and governance barriers (Yang et al., 2022).

The emerging consensus is that while side-effect-reducing democratization (PBS, MEV-Boost) redistributes some GEV, only protocol-level prevention—ensuring governance actors cannot unilaterally extract latent value—can protect fairness, liveness, and decentralization in future blockchains.

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References

• "FairFlow Protocol: Equitable Maximal Extractable Value (MEV) mitigation in Ethereum" (Sarkar, 2023)
• "Extracting Godl [sic] from the Salt Mines: Ethereum Miners Extracting Value" (Piet et al., 2022)
• "LØ: An Accountable Mempool for MEV Resistance" (Nasrulin et al., 2023)
• "MEV Sharing with Dynamic Extraction Rates" (Braga et al., 2024)
• "Unraveling the MEV Enigma: ABI-Free Detection Model using Graph Neural Networks" (Park et al., 2023)
• "A Flash(bot) in the Pan: Measuring Maximal Extractable Value in Private Pools" (Weintraub et al., 2022)
• "Certifying optimal MEV strategies with Lean" (Bartoletti et al., 16 Oct 2025)
• "Price of MEV: Towards a Game Theoretical Approach to MEV" (Mazorra et al., 2022)
• "CoMMA Protocol: Towards Complete Mitigation of Maximal Extractable Value (MEV) Attacks" (Churiwala et al., 2022)
• "MAD-DAG: Protecting Blockchain Consensus from MEV" (Bar-Zur et al., 26 Nov 2025)
• "Optimal MEV Extraction Using Absolute Commitments" (Landis et al., 2024)
• "The Specter (and Spectra) of Miner Extractable Value" (Angeris et al., 2023)
• "Maximal Extractable Value Mitigation Approaches in Ethereum and Layer-2 Chains: A Comprehensive Survey" (Alipanahloo et al., 2024)
• "SoK: MEV Countermeasures: Theory and Practice" (Yang et al., 2022)