Anti-Sybil Protection
How Drawi ensures fairness, eliminates Sybil attacks, and prevents exploitation.
Drawi is built for trustless, decentralized giveaways, but without proper security, on-chain raffles can be manipulated by bots, Sybil attackers, and reward farmers. To ensure fair participation, Drawi implements multi-layered security mechanisms that protect against abuse while maintaining an open and permissionless system.
1. Sybil Attack Prevention
A Sybil attack occurs when a single entity creates multiple fake accounts to manipulate a system. In a giveaway context, this means bot farms attempting to flood replies with low-effort responses to maximize their chances of winning.
How Drawi Mitigates Sybil Attacks
AI-Based Identity Verification → Analyzes behavioral patterns to detect fake accounts.
Wallet Address Uniqueness Checks → Flags duplicate addresses used across multiple accounts.
Participation Scoring System → Prioritizes real users over bots based on engagement history.
Cross-Contest Tracking → Identifies repeat offenders gaming multiple giveaways.
Example: AI-Based Sybil Detection
Scenario: A bot farm generates 100 accounts to reply with low-quality responses.
AI detects unnatural response patterns (similar wording, timestamps, engagement).
Wallet clustering analysis flags duplicate addresses.
System automatically excludes flagged entries from winner selection.
Only legitimate users remain eligible, ensuring a fair contest.
2. Bot Detection & Spam Filtering
Drawi’s AI continuously monitors response quality, engagement, and authenticity to prevent bot spam from flooding contests.
Key Detection Methods:
NLP & Sentiment Analysis → Filters out low-effort, copy-paste, and AI-generated spam replies.
Engagement-Based Trust Score → Accounts with organic likes, replies, and following history are prioritized.
Time-Based Anomaly Detection → Accounts mass-commenting instantly are flagged.
Wallet Reputation System → Identifies known farming wallets & prevents repeated abuse.
Example: Spam Filtering in Action
User
Response
Bot-Like Behavior Detected?
Eligible?
@RealUser1
“That’s hilarious, I love it”
No
Yes
@BotFarm47
“Nice!”
Short & generic
No
@CopyPaste89
“This is the best ever!!!” (Repeated across 20 replies)
Duplicate detected
No
@DegenChad69
“Here’s my meme + wallet: 0x123…”
High-quality engagement
Yes
Only high-quality, authentic participants are counted in the final draw.
3. Wallet Address Filtering & Anti-Farming Mechanisms
Many bot farms attempt to use multiple wallets to bypass detection. Drawi implements on-chain wallet analysis to block known farming operations.
Duplicate Wallet Detection → Flags users submitting the same wallet across multiple accounts.
Blacklist of Farming Addresses → Continuously updates known bot wallets.
Transaction History Check → Identifies suspicious wallet activity.
Example: Wallet Clustering Analysis
Bot farm detected: 10 Twitter accounts submitting responses with the same wallet → All disqualified. Legit user detected: Unique wallet used, verified engagement → Eligible for the draw.
4. Rate Limiting & API Security
Since Drawi’s AI interacts with Twitter & blockchain APIs, it enforces strict rate limits to prevent abuse.
API Rate Limits → Prevents mass participation from automated scripts.
ReCAPTCHA & Human Verification → Ensures real users participate in off-chain interactions.
Smart Contract Guardrails → Limits excessive on-chain calls to prevent spam.
Example of API Rate Limiting in Action: Scenario: A bot tries to send 500 responses within 5 minutes.
System detects abnormal request volume & blocks IP.
Account flagged as spam & blacklisted.
Real users continue participating normally.
5. On-Chain Transparency & Fairness
Unlike traditional giveaways where results can be manipulated, Drawi’s security model is fully transparent.
Provably Fair Selection → Uses decentralized thought for tamper-proof randomness.
On-Chain Distribution Records → Every payout is verifiable on Solana Explorer.
No Human Intervention → AI & smart contracts handle 100% of the process.
Proof-of-Fairness Example:
All eligible participants are recorded on-chain.
Decentralized thought choose.
The smart contract selects a winner & executes payout automatically.
Users can verify the transaction history publicly.
Final Result: A system that cannot be rigged, cannot be farmed, and cannot be manipulated.
Why This Matters
Most Web3 giveaways fail due to:
Bots & Sybil attackers → Fake users winning repeatedly.
Rigged, centralized draws → No way to verify fairness.
Spam-filled engagement → No quality control.
Drawi solves all these problems with an AI-driven, anti-bot, fully decentralized, and 100% transparent contest system. This raises the bar for fairness in Web3 giveaways.
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