Avoiding Bans in Web3: A Practical Anti-Sybil Airdrop Guide

Airdrop farming is a key strategy for Web3 users to gain wealth effects at low cost. However, project teams’ "Anti-Sybil mechanisms" act like invisible scythes—one misstep could lead to address bans or even blacklisting across networks. As a seasoned airdrop hunter, have you encountered these scenarios?

• Addresses with hard-earned interactions labeled as "Sybil," resulting in zero airdrop rewards;

• Multiple accounts under the same IP detected and wiped out by risk control systems;

• Automated scripts with low efficiency, while manual operations struggle to scale...

This guide reveals the core logic behind airdrop anti-Sybil systems and provides a low-cost, high-success-rate anti-detection strategy.

1. How Do Projects Screen Sybil Addresses? 3 Pitfalls You Must Avoid

Airdrop projects typically target Sybil clusters through three dimensions:

1. IP & Device Fingerprinting

• Batch address creation or transactions under the same IP (especially during popular airdrop campaigns);

• Repeated browser fingerprints (Canvas fingerprint, WebGL fingerprint, timezone/language settings);

• Hardware device IDs (e.g., phone IMEI, PC MAC address) linked to multiple wallets.

2. On-Chain Behavior Patterns

• Concentrated fund flows (e.g., all Gas fees sourced from a single intermediary address);

• Excessively regular transaction intervals (e.g., interactions at fixed daily times);

• Monotonous behavior (only interacting with target protocols, no other on-chain activity).

3. Social & Identity Data

• No domain/DID bindings (e.g., ENS, .bit) or linked social accounts (Twitter/Discord);

• Using bots for community tasks (e.g., auto-retweeting tweets, bulk joining groups).

Case Study: A user deployed 10 addresses for a Layer2 airdrop, but all were flagged as Sybil due to interactions via the same AWS server IP, resulting in a $50k+ potential loss.

2. Anti-Sybil Quad Methodology: Low-Cost Disguise as "Real Users"

Step 1: IP Isolation — Sever Address Correlations

Core Principle: One address = One unique IP.
Solutions:

• Residential Proxies: Use IPFoxy to obtain global static residential IPs (avoid datacenter IPs).

• IP Rotation: Rotate IPs before each on-chain interaction (leverage IPFoxy’s API for on-demand switching).

• Hybrid IP Usage: Combine proxy IPs with home broadband IPs to avoid 100% proxy reliance.

Step 2: Device Fingerprint Obfuscation — Ensure Address "Independence"

Basic Setup:

• Isolate accounts across browsers (Chrome/Firefox/Brave);

• Clear Cookies & LocalStorage after each session.

Advanced Tactics:

• Use fingerprint browsers (Multilogin, AdsPower) for isolated environments per address;

• Modify browser fingerprints (screen resolution, timezone, language);

• Disable WebRTC to prevent IP leaks (use plugins like WebRTC Leak Prevent).

Step 3: Mimic Human Behavior — Ditch "Bot Patterns"

Randomize Timing: Set interaction intervals between 15 mins–6 hrs (use Python’s random library for delays).

Diversify Funding Paths:

• Source initial Gas from different exchanges (e.g., Binance → Address A, OKX → Address B);

• Conduct periodic transfers between addresses to simulate organic activity.

• Engage with On-Chain Ecosystems: Randomly interact with other DApps (e.g., Uniswap swaps, OpenSea NFT browsing).

Step 4: Social Identity Binding — Build "Human Proof Chains"

Bind Decentralized IDs: Register ENS/SPACE ID domains per address, link to unique emails (ProtonMail/Tutanota).

Complete Community Tasks:

• Manually verify Discord roles, retweet tasks on Twitter;

• Create unique social profiles per account (avoid duplicate bios/avatars).

4. Pitfall Alerts: What NOT to Do

❌ Use a single MetaMask wallet to derive multiple addresses (HD Wallet paths expose links);
❌ Fund all addresses from the same exchange account;
❌ Run multiple instances on VMs/VPS (hardware fingerprints overlap);
❌ Skip tests: Always test paths with 0.001 ETH before interactions.

5. Conclusion

The essence of anti-Sybil defense is "making machines believe you’re human." By layering IP isolation, fingerprint obfuscation, and behavioral randomization, you significantly reduce ban risks. Remember: Project teams continuously upgrade their risk algorithms. Stay technically vigilant to thrive in the airdrop arena.