Kamon Index
Kamon Index is an identity and reputation API built for the Ninja API Forge.
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Description
Kamon Index: Trust & Identity for Injective
Frontend for testing : https://kamon-client.vercel.app (debug disabled)
Overview
Kamon Index is a developer-first Trust Oracle that transforms raw Injective wallet activity and N1NJ4 signals into Sybil-resistant reputation scores. It helps dApps distinguish real users from bots via simple REST endpoints.
The Problem & Solution
The Problem: Injective projects struggle with fragmented on-chain data, bot spam, and the lack of a standardized wallet reputation system.
The Solution: A unified trust layer that analyzes wallet maturity, economic stake, activity, and governance participation to provide:
Trust Scores (0–100): Deterministic reputation rankings.
Risk Levels: LOW (65+), MEDIUM (35-64), and HIGH (<35).
Bot Probability: AI-driven intent classification.
Signed Attestations: Secure JWTs for on-chain/off-chain verification.
Key API Endpoints
Endpoint | Purpose | Key Data Returned |
| Full profile | Score, Risk Level, Bot %, Tags, JWT |
| Wallet A/B testing | Determines "Winner" based on activity/stake |
| Transparency | Raw signal breakdown (Developer Mode) |
| Status | API uptime check |
N1NJ4 Integration
Kamon Index uses N1NJ4 credentials as a primary identity anchor. Verified wallets receive:
Score Bonuses: Immediate boost to reputation.
Priority Access: Higher API rate limits.
Stronger Verification: Higher confidence for airdrops and voting.
Who It’s For
DAOs: Sybil-resistant voting and delegate reputation.
Social dApps: Anti-spam moderation and user ranking.
DeFi: Bot-filtering for incentives and copy-trading filters.
Developers: Plug-and-play infrastructure using Node.js, TypeScript, and Injective LCD.
Kamon Index replaces custom anti-sybil logic with a single, scalable API, turning raw blockchain data into actionable intelligence.
Progress During Hackathon
Hackathon Progress
Designed Kamon Index as a reusable trust & identity infrastructure layer for Injective
Researched Injective data sources and stabilized on LCD-based analytics
Built modular data collectors for wallet activity, balances, staking, and governance
Implemented explainable trust scoring engine (0–100) with risk classification
Integrated N1NJ4 identity signals into reputation model
Added JWT-based signed attestations for verifiable trust profiles
Developed wallet comparison endpoint for side-by-side reputation analysis
Implemented developer debug mode with gated access
Deployed backend to production environment (Render)
Built and deployed public demo frontend for judge testing
Wrote comprehensive technical documentation and API references
Performed end-to-end testing on real Injective wallets
Fundraising Status
NONE