According to an in-depth report from the team of experts at Tan Phat Digital, the strong development of distributed ledger technology has redefined the concept of digital ownership. However, the permissionless nature of networks like Bitcoin, Ethereum and Solana has created vulnerabilities for transaction spam. Junk transactions are not only unwanted requests but also attack tactics that overload the system. By sending large volumes of fake requests, spam actors exhaust bandwidth, slow down confirmation speeds, and push gas fees to extreme levels, causing economic exclusion of real users.
Spam transactions affect the blockchain through a chain of knock-on effects, starting with network layer congestion, leading to skyrocketing transaction fees and causing disruption to decentralized applications (dApps). For network nodes, this burden is reflected in the consumption of storage and processing resources, threatening long-term decentralization. Although the fee mechanism is a natural barrier, sophisticated attacks still exploit structural flaws to undermine user trust.
Classification and technical mechanism of spam transactions in the Blockchain ecosystem
To understand how spam impacts, it is essential to analyze the mechanism behind it. Spam transactions are often divided into two groups: unintentional inefficiencies and targeted attacks.
Traditional forms of spam on the Bitcoin network
In the Bitcoin network, spam is often related to non-optimization, for example not using the sendmany command. When sending payments to many people at the same time using a series of single transactions instead of combining them, users create a large amount of redundant variable output, wasting network resources.
In addition, embedding non-financial data into transactions is also considered spam. Ultra-low-fee flooding attacks are a common tactic, where tens of thousands of near-zero-fee transactions are sent simultaneously, confusing users and consuming node bandwidth.
The Rise of Inscriptions and Ordinals on Bitcoin
The Ordinals protocol launched in 2022 allows embedding data directly onto satoshis. Even though they are valid transactions, they are often considered spam due to bloating block sizes and requiring permanent storage of non-financial data.
Comparison of Traditional Transactions and Inscriptions characteristics:
Data storage location: Traditional transactions are stored in Outputs/UTXO, while Inscriptions are stored in Witness Fields (Witness) field).
Fee mechanism: Traditional transactions follow standard market fees, Inscriptions enjoy SegWit discounts up to 75%.
Storage impact: Traditional transactions are low (only save balance/signature), Inscriptions are very high (save multimedia files).
Intended use: Traditional transactions to transfer financial value, Inscriptions to create native NFTs on-chain (Digital Artifacts).
MEV Spam: Algorithmic Wars at Layer 2 and Solana
A sophisticated form that is dominating high-performance networks is MEV Spam. Due to low costs and fast block times, MEV bots send a series of "blind" transactions to compete for arbitrage or liquidation priority. Research shows that on the Base network, MEV bots consume more than 50% of total gas but contribute less than 10% of transaction fees, creating a "spam wall" that neutralizes scaling benefits.
Impact of junk transactions on network node infrastructure and system resources
Junk transactions put direct pressure on hardware - the backbone of decentralization. Every node must validate and store every transaction, regardless of purpose.
Exhaustion of RAM and CPU processing power
When large-scale spam occurs, the mempool swells causing nodes to consume RAM to maintain the queue. If the limit is exceeded, the node software may experience a memory overflow error and crash. On the Solana network, spam from NFT minting bots once caused validators to run out of memory and downtime for hours. Validating millions of fake signatures also creates a huge CPU load, increasing block latency and threatening consensus.
Permanent ledger bloat and storage burden
"Ledger bloat" is the most dangerous effect. Due to immutability, every garbage transaction in the block must be permanently stored by full nodes. On Ethereum, storage node storage requirements have reached Terabyte levels. As hardware barriers increase, the number of node operators decreases, weakening decentralization.
Impact on system resources:
Bandwidth (Network): Causes transmission congestion and slow synchronization between nodes through P2P garbage data dissemination.
Memory (RAM): Causes memory overflow and node software crashes due to storage large number of transactions in the Mempool.
Processing (CPU): Increased block generation latency and reduced actual TPS due to signature validation and junk script code.
Storage (Disk): Bloated chain size and increased node maintenance costs due to permanent writing of junk data to the ledger.
See also: Why are Blockchain transactions pending for so long
Economic consequences and network congestion for real users
The network operates on an auction mechanism. cubic space. When spam fills the block, users with real needs have to pay higher fees to get priority.
The Explosion of Gas Fees and Financial Access Barriers
The most direct impact is to push gas fees up. In Ethereum, the address poisoning event in early 2026 exploited low fees after the Fusaka upgrade to send millions of junk transactions. As fees increase, microtransactions are no longer viable, causing "economic exclusion" of retail users.
Impact on the stability of the DeFi ecosystem
DeFi suffered the most. Lending protocols rely on liquidation bots to protect capital capacity. When the network is congested due to spam, liquidation orders are not confirmed promptly, leading to the accumulation of bad debt, threatening the stability of the on-chain financial system. The Oracle system can also crash when price updates are stuck in the mempool.
Economic and DeFi consequences:
Gas fee spikes: Causing increased transaction costs and eliminating retail users due to preferential auctions when blocks are full.
Confirmation delays: Causes payment inconvenience and affects user experience because of transactions valid stuck.
Liquidation failure: Causes bad debt accumulation and risk of DeFi protocol collapse due to bots not being able to execute orders.
Oracle bias: Causes asset loss due to trading based on old prices because price data is not updated promptly.
Analysis of sophisticated spam attacks: Address Poisoning
In the period 2025-2026, the form of address poisoning (address poisoning) explodes strongly on Ethereum and Layer 2.
Fraudulent mechanism through "dust" transactions
The attacker creates millions of wallet addresses with the same first/last character as the victim's address, then sends a very small amount of assets (dust). The goal is to "poison" the transaction history. When users copy addresses from their history to transfer funds without double-checking them, they accidentally send funds to the attacker. This is a form of industrial-scale social engineering thanks to the low cost of spam.
Impact of reducing gas fees on network security
The paradox after the December 2025 Fusaka upgrade is that the 60% fee reduction has reduced the cost of address poisoning attacks. Tan Phat Digital recorded that in January 2026, up to 2.7 million new addresses were created, an increase of 170% compared to normal levels. The financial losses were huge, with more than $740,000 stolen in a single month, including one loss of more than $509,000 by a single victim.
Case studies of network failure and resilience
Blockchain history is marked by many crises that spurred technological innovation.
Solana: Resilience 6 Tbps
While once vulnerable to IDO bots and NFTs in 2021, the 6 Tbps DDoS attack in December 2025 demonstrated Solana's maturity. The network remains stable with confirmations under 1 second thanks to defense layers such as:
QUIC Protocol: Flow control and garbage request offload.
Stake-Weighted QoS: Prioritize transactions from nodes with high stakes.
Local fee market:Prevents local network congestion from affecting the entire system.
Arbitrum and the Timeboost mechanism
Arbitrum introduces Timeboost to reduce latency racing and MEV spam across the "express lane". However, the reality is that 22% of priority transactions are still reversed, showing that bots continue to spam. This mechanism is also criticized for causing centralization when two entities account for more than 90% of winning auctions.
Natural defense mechanisms and advanced technical solutions
The fight against spam is not only about increasing fees but also changing the blockchain structure.
Outstanding technical solutions compiled by Tan Phat Digital:
EIP-1559 (Base Fee): Increases fees exponentially when the network is congested, making a sustained spam attack prohibitively expensive.
EIP-4844 (Blobs): Isolate temporary data space, preventing data spam from bloating the ledger permanently.
Parallel Execution: Concurrent execution of zero transactions collisions, helping to isolate the impact of spam to local areas.
Stake-Weighted QoS: Prioritizes traffic based on reputation and stake, ensuring transmission for valid transactions.
2026 Vision: Towards sustainability
The 2026 roadmap focuses on cleaning up technical debt caused by spam. Proposals like EIP-4444 (History Expiry) allow nodes to discard data older than one year, reducing storage pressure. Ethereum's Glamsterdam and Hegota roadmaps promise increased gas limits and the implementation of Verkle Trees for lighter node runs.
At the same time, local reputation models like STARVESPAM are being explored. Instead of global fees, the node itself builds a reputation score for the entity sending the transaction, helping to filter spam from the source without increasing costs for honest users.
10 Typical Case Studies on Spam Transaction and Consequences
To clearly illustrate the above impacts, Tan Phat Digital compiles 10 typical real-life cases that have reshaped blockchain history:
1. Solana: 6 Tbps DDoS attack (December 2025)
Background: The largest DDoS attack in blockchain history targeted Solana for 7 consecutive days.
Technical impact: Traffic peaked at 6 Tbps with billions of packets per second. However, thanks to QUIC and SWQoS, the network still maintains confirmation times under 1 second.
Conclusion: Demonstrates the effectiveness of filtering spam at the network layer before it reaches the execution engine.
2. Ethereum: Address Poisoning crisis after Fusaka upgrade (January 2026)
Context: Taking advantage of the 60% reduction in gas fees after the Fusaka upgrade, attackers created 2.7 million fraudulent addresses.
Economic impact: 116 victims lost more than 740,000 USD. An individual lost up to 509,000 USD due to mistakenly copying an address that looked similar from transaction history.
Conclusion: Low gas fees are a double-edged sword, reducing the cost of large-scale phishing attacks.
3. Yuga Labs: Otherside NFT Mint Incident (April 2022)
Context: The "Otherdeeds" metaverse land sale created a record fever on Ethereum.
Technical impact: Gas fees skyrocketed to 6,000-8,000 Gwei. Users spent 170 million USD (60,000 ETH) on gas fees alone, including 14,000 failed transactions causing a loss of 5 million USD in fees.
Conclusion: Suboptimal NFT mints can cripple the network and cause huge economic losses to users.
4. Arbitrum: Failure of the Timeboost mechanism (Year 2025)
Context: Arbitrum deploys Timeboost to reduce MEV spam through "express lane" priority auctions.
Technical impact: 22% of transactions in the express lane are still reversed, showing that bots are still spamming blindly. More than 90% of winning auctions belong to just 2 entities.
Conclusion: Fee auction mechanisms do not always address spam and pose a risk of centralization.
5. Polygon: Decision to raise minimum fees to 30 Gwei (October 2021)
Background: Polygon was flooded by junk transactions with fees of only 1 Gwei, accounting for 90% of network capacity.
Technical impact: Network raised fees to 30 Gwei, immediately reducing the amount of junk transactions 75% (from 2 million to 500 thousand transactions/day).
Conclusion: Minimal economic barriers are the crude but most effective solution to prevent cheap spam bots.
6. Solana: Grape Protocol IDO incident (September 2021)
Context: Bots flooded the network to gain the right to buy tokens during the IDO on Raydium.
Technical impact: Bot traffic exceeded 4 million transactions/second, causing memory overflow at validators. The network was down for 17 hours.
Conclusion: This issue forced Solana to rewrite the network protocol from UDP to QUIC for flow control.
7. Bitcoin: Ordinals and Inscriptions Fever (2023)
Context: Users began embedding millions of image and text files directly into Bitcoin.
Technical impact: Caused the longest period of network congestion in Bitcoin history. The average block size increased from 1.2MB to nearly 2.5MB permanently.
Conclusion: Non-financial data embedded on-chain is a form of spam that bloats the ledger without end.
8. BNB Chain: Record transaction during Inscription (December 2023)
Context: Inscription fever spread to BNB Chain.
Technical impact: Recorded 32 million transactions in a single day (December 7, 2023). Although the network did not collapse, gas fees have increased many times the normal level.
Conclusion: Layer 1 EVM networks can handle the load well but still face great cost pressure when spammed.
9. Avalanche: Network congestion due to ASC-20 (January 2024)
Context: The emergence of the ASC-20 inscription standard attracted a large number of token minting bots.
Technical impact: More than 100 million inscriptions were minted, pushing daily gas fees to 5.6 million USD.
Conclusion: Shows that even networks with modern architecture are still vulnerable to inscription spam trends.
10. Base/Layer 2: "MEV Spam Wall" (Period 2024-2025)
Context: MEV bots race to arbitrage on the Base network (Layer 2 of Ethereum).
Technical impact: Bots consume 56% of the gas but pay only 14% of the fees. When the network increases capacity, bots immediately increase the amount of spam to "fill" the empty space.
Conclusion: MEV spam is "neutralizing" the benefits of scaling, preventing fees for real users from being reduced further.
Frequently Asked Questions (FAQs) about Junk Trading on Blockchain
Here are the 15 most common questions related to spam transaction is answered by Tan Phat Digital based on the latest research data:
1. What is spam transaction? These are unnecessary or ineffective transactions sent in bulk to cause network congestion, push up gas fees or overflow the memory (mempool) of network nodes.
2. Why is Bitcoin spammed even though transaction fees are quite high? Many forms of spam on Bitcoin come from not optimizing the source code (for example, not using sendmany) or using the network to transmit non-financial data, leading to waste of resources.
3. Are Ordinals and Inscriptions considered spam? Technically, they are valid transactions. However, many experts consider these to be spam because they embed large data (images, videos) into the ledger, causing permanent bloat in the chain size.
4. How does MEV spam affect regular users?
MEV bots continuously submit thousands of transactions to compete for arbitrage rights. This pushes up base gas fees, causing real users to pay more for simple transactions.
5. How does the EIP-1559 mechanism protect the network from spam? EIP-1559 applies a base fee that automatically increases exponentially if the block is full. This makes sustained spam attacks extremely expensive and economically unfeasible.
6. Why will Address Poisoning explode so strongly in 2026? Fusaka upgrade helps extremely low transaction fees, unintentionally reducing the cost of sending millions of "dust" transactions to poison users' wallet history.
7. Can junk transactions crash network nodes? Yes. If the amount of spam exceeds the RAM or CPU's processing capacity, the mempool will overflow, resulting in the node software crashing or disconnecting itself.
8. How dangerous is "Ledger bloat"? When garbage is permanently written to the ledger, the storage capacity required for a node will skyrocket (reaching Terabyte levels), causing fewer people to be able to run the node, thereby reducing decentralization.
9. Why are DeFi protocols vulnerable to spam? When the network is congested, important liquidations are not confirmed in a timely manner. This can cause bad debt to accumulate and collapse lending protocols.
10. How did Solana withstand the 6 Tbps attack? Thanks to the implementation of the QUIC protocol for traffic control and the Stake-Weighted QoS mechanism that helps prioritize transactions from large reputable (stake) entities.
11. Does EIP-4844 (Blobs) solve the data spam problem? Blobs separate temporary Layer 2 data from Layer 1. After about 18 days, this data is deleted, helping to prevent data spam from bloating the permanent ledger.
12. How can individuals avoid address poisoning scams?
Absolutely do not copy addresses from recent transaction history. Always use a verified address book or carefully check each character of the wallet address.
13. What is the role of proposed EIP-4444 (History Expiry)?It allows nodes to discard historical data older than one year, helping to reduce storage burden and address technical debt due to accumulated spam from the past.
14. How does parallel processing (Parallel Execution) help in fighting spam?This mechanism isolates spam transactions into separate processing threads, preventing a spammed smart contract from clogging all other applications' operations.
According to an assessment from Tan Phat Digital, spam transactions are an inevitable challenge for open systems. However, through attacks, the network has become more resilient. The shift to complex mechanisms like EIP-1559, parallel processing, and blobs is key to scaling while remaining secure. In the future, a combination of economic barriers and technical measures such as state expiration will protect the blockchain, ensuring block space is always reserved for real economic value.
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