Personalized risk profiles for student NFT portfolios
University students are repeatedly falling victim to scams and rug pulls in web3 projects, resulting in significant financial losses during NFT trading attempts.
SafeNFTScore connects your wallet to generate custom risk profiles, predicting rug potential based on project traits and your trading history. It simulates trade outcomes and suggests safe alternatives. Designed for uni budgets with loss-limiting strategies.
University students new to web3 and actively exploring NFT trading
Behavioral AI adapting to your risk tolerance from past (simulated) trades
professional
Auto-generate risk score for connected wallet holdings
Test 'what-if' buys with projected rug odds
Suggest low-risk NFTs matching your profile
Log past scans to refine your AI profile
Set student-budget limits with auto-stop loss alerts
Weekly personalized scam trend forecasts
PDF risk summaries for sharing
One-click safe swaps
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| wallet_address | text | No |
| risk_tolerance | int | No |
| budget_limit | int | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| overall_risk_score | int | No |
| last_updated | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| project_address | text | No |
| projected_loss | int | No |
| simulated_at | timestamp | No |
Relationships:
/api/profileGenerate/update wallet risk profile
/api/simulateRun trade outcome simulation
/api/recommendationsFetch safe NFT suggestions
/api/historyList past simulations
/api/budget-alertsUpdate and check budget limits
No recs or history
N/A
N/A
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 150 | 2.5% | $45 | $540 |
| Month 6 | 1,200 | 5% | $720 | $8,640 |
Wallet risk profiles and sims prevent rugs tailored to your style
Target Twitter ads to 'NFT student' searches ($100 budget); partner with 2 uni web3 newsletters for trials; interview 10 students via LinkedIn for custom profiles as hooks.
Portfolio tracking
No predictive scam sims
Student AI personalization
User trading data flywheel for better AI
Walletconnect adoption surging, students entering with ETH ETF inflows
Wallet API rate limits
Caching + Alchemy
Prediction inaccuracies
Clear disclaimers
AI training data
Start with pre-trained models
Success: 85% find useful
Success: 3 sims/user/week
Success: >3%
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