🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators, with no network calls, shell executions, obfuscations, or credential risks detected. The metadata risk is slightly elevated due to the author's limited activity on PyPI.

No network calls detected.
No shell execution patterns found.

Per-check LLM notes

Network: No network calls detected, which is normal for a MySQL database interaction package unless it requires external services.
Shell: No shell execution patterns detected, which is expected as direct shell access is not typical for a database interaction library.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
Metadata: The author has only one package and lacks PyPI classifiers, suggesting low effort or inactivity.

🔬 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

Repository yaogdu/AgentLedger appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "AgentLedger Contributors" 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 agentledger-mysql

Create a mini-application called 'Transaction Tracker' that allows users to manage their financial transactions using the 'agentledger-mysql' package. This application will serve as a simple ledger where users can add new transactions, view past transactions, and calculate balances. Here’s a detailed breakdown of the steps and features:

1. **Setup Environment**: Ensure your environment is set up with Python 3.x and install necessary packages including 'agentledger-mysql'.
2. **Database Initialization**: Use 'agentledger-mysql' to initialize a MySQL database schema specifically designed for storing transaction data.
3. **User Interface**: Develop a basic command-line interface (CLI) for user interaction.
4. **Add Transactions**: Implement functionality to add new transactions to the ledger. Each transaction should include fields like date, description, amount, and category (e.g., groceries, rent).
5. **View Transactions**: Allow users to view all transactions or filter them by date range or category.
6. **Balance Calculation**: Enable the application to automatically calculate the current balance based on the sum of all transactions.
7. **Backup and Restore**: Integrate a feature that allows users to backup their ledger data to a file and restore it later.
8. **Security Measures**: Ensure that sensitive information such as passwords used to connect to the MySQL database are handled securely.
9. **Testing**: Write unit tests to verify that each feature works as expected.

The 'agentledger-mysql' package will be crucial in managing the state of the ledger within the MySQL database. It will handle the storage and retrieval of transaction records, ensuring consistency and reliability of the ledger data.