🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is generally low-risk due to its minimal network and shell execution requirements. However, the metadata risk, particularly the lack of detailed maintainer information, raises concerns about potential supply-chain risks.

Metadata risk due to an inactive or new maintainer account
Lack of proper author details

Per-check LLM notes

Network: No network calls are expected if the package is solely designed to interact with Monzo API locally and does not require additional external services.
Shell: No shell executions are expected in a standard Python library that interacts with an API.
Metadata: The maintainer has a new or inactive account and lacks a proper author name, which raises some suspicion but not enough to conclusively determine malice.

🔬 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

Email domain looks legitimate: petermcdonald.co.uk>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository petermcd/monzo-api appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with Monzo-API

Create a personal finance tracker app using the Monzo-API Python package. This app will allow users to monitor their spending habits, categorize transactions, and set budget limits for different categories of expenses. Here are the steps and features you should include in your project:

1. **Setup**: Begin by installing the Monzo-API package and setting up authentication with Monzo Bank's API. Ensure that you have the necessary permissions and API keys from Monzo.
2. **Data Fetching**: Implement functionality to fetch transaction data from the user's Monzo account. Use the Monzo-API to retrieve all recent transactions and store them locally in a structured format such as a SQLite database.
3. **Transaction Categorization**: Develop an algorithm or use predefined categories provided by Monzo to categorize each transaction into specific types like groceries, entertainment, bills, etc. This could involve machine learning if you want to automate the categorization process.
4. **Budget Setting**: Allow users to set monthly budgets for different categories. For example, they might want to limit their grocery spending to £100 per month. Track the total spent in each category against these budgets.
5. **Visualization**: Create visual representations of spending patterns over time. Use libraries like Matplotlib or Plotly to generate graphs showing daily, weekly, and monthly spending trends.
6. **Notifications**: Implement a feature where users receive notifications when they exceed their budget in any category. These notifications could be via email or SMS, depending on the user's preference.
7. **User Interface**: Design a simple and intuitive user interface using a framework like Flask or Django. The UI should display key information about the user's finances in real-time, allowing them to easily monitor their spending habits.
8. **Security**: Ensure all user data is handled securely, especially sensitive financial information. Follow best practices for securing web applications and protecting user data.

By following these steps, you'll create a comprehensive tool that helps users manage their finances more effectively using the Monzo-API package.