Mempool Flooding

The primary goal is to deny service to legitimate users by saturating the mempool. This creates a backlog, causing:

• Increased confirmation times for regular transactions.
• Spikes in transaction fees as users compete for block space.
• Potential temporary network paralysis, degrading the user experience and trust in the chain.

Attackers flood the mempool with their own transactions to manipulate transaction ordering for profit. Key techniques include:

• Priority Gas Auctions: Bidding up gas prices to ensure a target transaction (e.g., a large DEX swap) is processed adjacent to their own.
• Sandwich Attacks: Placing one transaction before and one after a victim's swap to profit from the resulting price movement.
• Mempool congestion makes these predatory strategies more effective by obscuring the victim's transaction.

Flooding can be used to stress-test or manipulate network consensus, particularly in Proof-of-Stake systems. Goals include:

• Testing validator resilience and network throughput limits.
• Attempting to induce validator slashing by causing them to miss blocks or propose invalid ones under load.
• Creating conditions for chain reorganizations by delaying block propagation, though this is highly resource-intensive.

By artificially inflating demand for block space, an attacker can manipulate the base fee (in EIP-1559 chains) or general fee market. Potential motives are:

• Increasing protocol revenue from fee burns if holding a related asset.
• Forcing economic pressure on competitors or specific dApps that rely on predictable transaction costs.
• Creating a false signal of high network activity.

Mempool flooding can act as a smokescreen for a separate, critical attack. While network operators and users are distracted by the congestion, the attacker may:

• Execute a flash loan attack or governance exploit on a decentralized protocol.
• Perform large-scale arbitrage that might otherwise be noticed and front-run.
• The noise makes it harder to detect and react to the primary malicious transaction in real-time.

In some cases, flooding is a form of protest or an attempt at extortion. An actor might:

• Threaten continued spam unless a ransom is paid (a rare but documented occurrence).
• Protest against protocol decisions or governance outcomes by disrupting normal operation.
• Demonstrate a vulnerability publicly to force a fix, acting as a white-hat stress test.

The attacker generates and propagates a high volume of transactions, often with zero or minimal fees, to fill the mempool of network nodes. This creates a backlog, increasing transaction confirmation times for legitimate users and consuming node resources for validation and storage. The goal is to create artificial congestion without incurring significant cost.

Flooding attacks aim to achieve several disruptive outcomes:

• Denial-of-Service (DoS): Render the network unusable for regular users by maxing out block space and node memory.
• Fee Market Manipulation: Force legitimate users to pay higher gas fees or priority fees to outbid the spam.
• Preparation for Front-Running: Create a crowded mempool to obscure targeted transactions before a sandwich attack or other MEV extraction.

Observable effects of a mempool flood include:

• Skyrocketing Average Fees: As users compete for limited block space.
• Increased Pending Transaction Count: Mempool size grows exponentially.
• Node Performance Degradation: Increased CPU, memory, and bandwidth usage can cause nodes to fall out of sync.
• User Experience Collapse: Wallets fail to estimate accurate fees, and transactions remain stuck for hours or days.

Networks and node operators employ several defenses:

• Minimum Fee Requirements: Nodes can set a minimal gas price to accept transactions, filtering out zero-fee spam.
• Mempool Limits: Enforcing size or count limits on the mempool, with eviction policies for the lowest-fee transactions.
• Transaction Gossip Rules: Protocols like Ethereum's txpool management and peer scoring to penalize nodes propagating spam.
• Fee Market Algorithms: EIP-1559's base fee mechanism provides some inherent resistance by dynamically burning fees from spam.

A subset of flooding where an attacker sends tiny amounts of a native token or ERC-20 tokens to a vast number of addresses. While not always congesting the mempool, it:

• Clutters wallet histories and UTXO sets.
• Can be used for chain analysis and address clustering.
• May be a precursor to phishing or scam attempts targeting the dusted addresses.

A historical case where attackers exploited low gas costs for certain opcodes (like EXTCODESIZE and BALANCE) to create computationally cheap transactions that were expensive for nodes to process. This flooded the mempool and caused Geth and Parity clients to crash, leading to significant protocol upgrades and gas cost re-pricing in subsequent hard forks.

A sustained spam attack on the Bitcoin Cash (BCH) and later Bitcoin SV (BSV) networks. Attackers broadcasted hundreds of thousands of tiny, dust transactions to fill blocks and bloat the UTXO set. The goal was to increase node operational costs and disrupt network usability, demonstrating how cheap transaction fees on high-throughput chains can be exploited for denial-of-service.

A sophisticated attack where an actor flooded the Arbitrum sequencer inbox with a massive volume of transactions. This mempool spam aimed to exploit a race condition in transaction ordering to gain a financial advantage in a pending airdrop. The event caused a temporary sequencer outage and led to protocol improvements for handling inbox congestion and transaction ordering fairness.

Repeated incidents, notably around popular NFT mints, where arbitrage bots and users spam the network with millions of transactions per second. This mempool flooding overwhelms the network's leader schedule, causing widespread transaction failure and degraded performance. These events have driven the development of solutions like localized fee markets (priority fees) and QUIC protocol implementation.

Mempool flooding is a tactical tool in Maximal Extractable Value (MEV) strategies. Searchers may flood the mempool with decoy transactions to:

• Obscure their target transaction from competitors.
• Create artificial congestion to delay rival arbitrage or liquidation bundles.
• Manipulate gas prices to influence transaction ordering. This turns the mempool into a competitive battlefield for block space.