🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across all categories with no network calls, shell executions, obfuscations, or credential harvesting. The metadata risk is slightly elevated due to the maintainer having only one package, but this alone does not suggest a supply-chain attack.

No network calls
No shell execution
No obfuscation patterns
No credential harvesting
Single package maintained

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external communication.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious shell command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package, which might indicate a new or less active account, but no other suspicious elements were found.

🔬 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: gmail.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "AndiEcker" 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 aedev-app-tpls

Create a Python-based mini-application called 'ProjectStarter' which will streamline the process of setting up new development projects. This tool will utilize the 'aedev-app-tpls' package to provide users with predefined templates and configurations, ensuring a consistent and efficient setup process for various types of projects. Here are the steps and features for your application:

1. **User Interface**: Develop a simple command-line interface (CLI) that allows users to interact with the application. Users should be able to specify the type of project they wish to start (e.g., web app, data analysis, machine learning).
2. **Template Selection**: Use the 'aedev-app-tpls' package to load and display available project templates. These templates should include common structures and initial files needed for different types of projects.
3. **Configuration Customization**: Allow users to customize certain aspects of their project, such as project name, version number, author details, etc., directly within the CLI. Ensure these customizations are reflected in the generated project files.
4. **Dependency Management**: Integrate with 'pip' to automatically install necessary dependencies based on the selected template. Provide options for users to add or remove specific packages.
5. **Post-Setup Actions**: After setting up the project, the application should provide a summary of the actions taken and any additional steps the user might need to perform manually (e.g., database configuration).
6. **Documentation Generation**: Automatically generate basic documentation for the project, including README.md with a brief description, installation instructions, and usage examples.
7. **Testing Setup**: Set up a basic testing environment for the project, including test files and frameworks according to the project type.

To utilize the 'aedev-app-tpls' package, you'll need to import its modules to handle template loading, customization, and possibly configuration file generation. Make sure to document how each feature interacts with the package and how it contributes to the overall functionality of 'ProjectStarter'.