VEEPAY
by VEEPAYONX
Overview
Building and managing autonomous AI agents on the Solana blockchain for Web3 automation, decision-making, and modeling complex behaviors (e.g., whale cognition/financial trading).
Installation
python ai/api/server.pyEnvironment Variables
- SECRET_KEY
- JWT_SECRET
- DB_HOST
- DB_PORT
- DB_USER
- DB_PASSWORD
- DB_NAME
- REDIS_HOST
- REDIS_PORT
- REDIS_PASSWORD
- REDIS_DB
- RPC_URL
- RPC_HTTP
- RPC_WS
- PUMPFUN_PROGRAM_ID
- SOLANA_PRIVATE_KEY
- AI_MODEL_ENDPOINT
- WS_PORT
Security Notes
Multiple critical vulnerabilities observed: 1. Hardcoded default JWT secret keys are present in `ai/api/server.py`, `backend/api/handlers/user.go`, `backend/api/models/user.go`, `backend/api/models/agent.go`, and `backend/api/models/transaction.go`. These must be immediately replaced with secure, environment-variable-managed secrets. 2. In `backend/api/middleware/auth.go`, the JWT secret is fetched from an environment variable (`JWT_SECRET`) but no default is provided. If `JWT_SECRET` is unset, the secret becomes an empty string, rendering all JWTs easily forgeable and compromising authentication. 3. The `ai/api/endpoints.py` file contains a placeholder `get_current_active_user` function that explicitly returns `{"username": "placeholder_user"}` without validating the provided JWT token. If this module's routes are used with this local dependency, it completely bypasses authentication for critical AI model management (predict, retrain, upload models) and other API endpoints. 4. In `backend/websocket/server.go`, the `validateToken` function is hardcoded to `return token == "valid-token"`, allowing any client with this dummy token to access WebSocket services without proper authentication. These issues collectively make the system highly vulnerable to unauthorized access and manipulation.
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