🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity or obfuscation and does not execute shell commands or harvest credentials. It is considered safe for use.

No network calls detected.
No shell execution patterns found.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no direct system command risks.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (2840 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

○ Low Type Annotations 1.0

No type annotations detected

No type annotations, py.typed marker, or stub files detected

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aidu-ai-llm

Create a personal finance advisor app using the Python package 'aidu-ai-llm'. This app will help users manage their finances by providing personalized advice based on their spending habits and financial goals. The app should include the following features:

1. **User Registration & Authentication**: Allow users to sign up and log in securely.
2. **Expense Tracking**: Users can input their daily expenses (e.g., groceries, utilities, entertainment) with categories and amounts.
3. **Budget Planner**: Based on the user's income and expenses, the app should suggest a monthly budget plan.
4. **Savings Calculator**: Estimate how much the user can save each month if they adhere to the suggested budget.
5. **AI-Driven Advice**: Using the 'aidu-ai-llm' package, provide tailored financial advice such as investment tips, saving strategies, and ways to reduce unnecessary spending.
6. **Financial Goal Setting**: Users can set short-term and long-term financial goals (e.g., buying a house, retirement savings), and the app will provide actionable steps to achieve these goals.
7. **Notification System**: Send reminders and notifications about upcoming bills, savings progress, and any other important financial updates.

**How to Use 'aidu-ai-llm' Package**: 
- Integrate the package to analyze user data and generate personalized financial insights and advice.
- Utilize the package's LLM capabilities to process natural language queries from users about their finances and provide relevant responses.
- Implement machine learning models provided by 'aidu-ai-llm' to predict future financial trends based on historical data.