Forward the Original Title‘Harsh Reality: The Three Major Contradictions in the Current Airdrop Market’

Preface

The current airdrop market has become a ruthless competition driven purely by self-interest. On one hand, project teams tacitly allow data manipulation to attract funding, only to conduct large-scale purges before distributing airdrops. On the other hand, airdrop hunters engage in a high-stakes game of chance, caught in the dilemma of “If you farm, you might not get anything, but if you don’t farm, you’ll definitely get nothing.” This referee-less game exposes the most pressing contradictions in the airdrop market—the stark divide between inflated data and real value, and the conflict between short-term gains and long-term ecosystem sustainability. Leveraging data from 100 airdrop projects in 2024, Lao Dong unveils the latest trends and hidden rules of the airdrop game—Who is profiting? Who is being exploited?

1. Project Team’s Conflicting Goals💡

Core Conflict: The Need for Data Growth (Creating a Bubble) vs. Controlling Token Outflow (Eliminating the Bubble)

“We know that over 80% of the addresses belong to farming studios, but we still rely on them for the ecosystem’s initial traction.” — CTO of an L2 Protocol

Before the Token Generation Event (TGE), project teams face a tough dilemma:

• Creating the Bubble: They silently allow farming studios to inflate metrics such as Total Value Locked (TVL), transaction volume, and user count to present a thriving on-chain ecosystem and attract investors.
• Bursting the Bubble: Just before the airdrop, they conduct rigorous address filtering and mass purges to eliminate farming activity.

1. Data Analysis of Airdrop Types

Lao Dong has compiled the airdrop rules of 100 projects in 2024 and categorized the distribution of different airdrop types.

Based on project data analysis, interaction-based airdrops, NFT-holding airdrops, and points-based airdrops currently dominate the market as the three main mechanisms.

• Interaction-Based Airdrop: This is the most common type of airdrop, mainly occurring on testnets and mainnets. Projects design a series of tasks, such as Odyssey-style events, to boost on-chain interactions and TVL in order to attract funding. However, excessive interactions often lead to address purges by the project team. For example, LayerZero flagged 803,000 addresses as Sybils, Linea identified 40% of addresses as Sybils, and StarkNet labeled high-frequency interaction users as bots.
• NFT Holding Airdrop: The second major type of airdrop is based on NFTs or OATs (On-Chain Achievement Tokens), which often serve as airdrop eligibility proofs. Most of these require completing various tasks or obtaining whitelist access to mint the NFT (often requiring financial investment). These NFTs are tradeable on-chain, making them susceptible to insider trading risks. Projects can concentrate token supply, allowing for market manipulation (e.g., FUEL and Berachain NFTs had unfair airdrop allocations).
• Points-Based Airdrops: This increasingly popular method differs from token-based airdrops because points are centralized data that can be manipulated and non-transparent. Inflated infinitely or rules adjusted arbitrarily, raising concerns about fairness. For example, ME (Sybil addresses had their points reset to zero and exchange ratios varied), and Linea (LXP is an SBT, another form of points system, where even having tokens may not guarantee an airdrop). Points-based airdrops are also heavily suspected of insider trading (controversies like EigenLayer’s snapshot incident, Blast’s points inflation, and IO’s “points reduction and theft” disputes all suggest possible insider trading)

Other airdrop methods, such as staking, developer rewards, and voting-based distributions, serve as different ways for projects to filter recipients. However, lack of transparency, insider trading, and hidden rules continue to cast doubt on the fairness of airdrops in the current market.

2. Market Game Theory and Project Strategy Selection

The current market is a zero-sum game with limited resources, making it impossible to have everything. Project teams cannot simultaneously satisfy the interests of themselves, VCs, users, and exchanges, and must allocate benefits and extract value through dynamic game theory. Faced with the contradictions of airdrop incentives, project teams typically adopt two strategies:

• Universal Distribution Type: Suitable for small projects or those with generous rewards, like HYPT, with basically no filtering where every address receives rewards. These projects generally involve blind farming, have no clear airdrop rules, making it impossible to determine the risk-reward ratio, and struggle to attract large-scale operations
• Strict Screening Type: Suitable for large projects, typically screening users through points, interaction frequency, rankings, and Sybil detection, implementing a bottom-elimination system. For example, SCR (requiring 200+ points for airdrop eligibility), RuneStone (screening through inscription and NFT holdings), ZKsync and StarkNet (multiple condition screening), LayerZero (Sybil reporting system). While this strategy improves the precision of reward distribution, it also increases participation uncertainty, putting farmers at a disadvantage in the rules-based game

2. Participants’ Internal Conflict 🤔

Core Conflict: No participation means definitely no rewards vs. Participation doesn’t guarantee rewards

Participants also faced a dilemma:

• No participation means definitely no rewards: If you don’t participate in projects at all, you definitely won’t receive any airdrop rewards. To pursue potential returns, many users are forced to actively participate in various tasks and activities, investing significant time and resources, which further intensifies market competition and participant anxiety
• Participation doesn’t guarantee rewards: Even with maximum effort, rewards aren’t guaranteed. User input and output aren’t proportional, as project teams use various methods to filter addresses. Complex screening mechanisms cause many participants to lose airdrop eligibility due to strategic mistakes or being mistakenly labeled as Sybil accounts

1. Excessive Competition and Investment Risks

Users are forced to generate large amounts of data and activity to compete for limited rewards. However, complex and opaque rules combined with strict screening criteria make it difficult for participants to predict their actual returns.

Among 100 projects in 2024, 32 explicitly check for Sybil attacks. Most projects’ screening criteria are not public, and the review process is a complete black box operation controlled entirely by project teams, leaving users like lambs to the slaughter, subject to arbitrary judgment. Below is an analysis of Sybil types:

The core criteria for project teams to screen Sybil accounts include:

• Homogeneous interactions: Large numbers of similar operation patterns are the main reason for being identified as Sybil accounts
• Address clustering behavior: Multiple addresses performing similar operations at the same time and in the same environment are easily identified and liquidated
• IP, device, and frontend interactions: More and more projects analyze user behavior through frontend data, making simple IP and device switching counter-strategies ineffective

To survive in this airdrop game, funds and luck alone are far from enough. You also need more sophisticated interaction strategies, stronger technical support, enhanced counter-surveillance capabilities, and continuous investment and persistence.

3. The Conflict Between Project Teams and Farmers🤝

Core Conflict: Shared Loss VS Shared Prosperity

In the game of airdrop incentives, project teams and farmers have formed a “symbiotic” relationship with closely intertwined destinies:

• Shared prosperity: When both parties achieve a relatively balanced incentive mechanism, it can attract sufficient active data while ensuring ecosystem quality, benefiting both project teams and users;
• Shared loss: If either side becomes unbalanced, whether due to inappropriate airdrop strategies by project teams or excessive farming by users, it will ultimately negatively impact the entire ecosystem, and neither party can escape unscathed.

Dynamic Game Theory:

• When participating in airdrops, project teams usually set certain thresholds. For example, Linea’s POH verification and IP-based faucet thresholds. When project teams set loose participation thresholds, farmers can participate in large numbers, creating a short-term data surge, but once this bubble effect is cleared by strict screening mechanisms, the entire ecosystem may fall into a situation where data severely disconnects from actual user activity. For instance, after LayerZero announced the completion of its snapshot, the number of active on-chain addresses dropped precipitously
• Conversely, when project teams design rules with higher participation thresholds, they ensure that only truly active users who contribute real value can receive rewards. While such high thresholds may not lead to a surge in participants in the short term, they do result in healthy and stable growth of active on-chain addresses, avoiding the creation of data bubbles.

The essence of airdrops is a dynamic game of interests between project teams and users. For farmers to secure steady returns, they must refine their strategies, improve interaction quality, and even build long-term value; for project teams, they shouldn’t deliberately pursue financing or major exchange listings, and their core task shouldn’t be how to manipulate users to create short-term prosperity, but rather how to build a long-term sustainable ecosystem that truly provides value support.

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