🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential misuse due to its metadata and network risk, although there is no clear evidence of malicious activity.

Metadata risk due to a single package and lack of GitHub link
Moderate network risk with potential unexpected destinations

Per-check LLM notes

Network: The presence of network calls with timeout settings may be necessary for legitimate functionality but should be reviewed for unexpected destinations.
Shell: No shell execution patterns detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package and no linked GitHub repository, which may indicate a new or less active developer.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

imeout in seconds (see :func:`urllib.request.urlopen`). :return: empty string if t

✓ 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 ae-base

Create a mini-application called 'AE Weather Tracker' which integrates the 'ae-base' Python package to provide users with current weather conditions and forecasts for any given city. This application will utilize the OpenWeatherMap API to fetch real-time weather data and store it locally for offline viewing. The 'ae-base' package will be leveraged for its helper functions, context managers, and classes to manage data retrieval, caching, and user interaction.

Step-by-Step Instructions:
1. Set up a virtual environment and install necessary packages including 'ae-base', 'requests' for API calls, and 'pandas' for data manipulation.
2. Use the 'ae-base' package's context manager to handle file operations for storing weather data locally.
3. Implement a function using 'ae-base' helper functions to retrieve weather data from the OpenWeatherMap API for a specified city.
4. Develop a caching mechanism with 'ae-base' classes to save fetched weather data for future offline use.
5. Create a user-friendly interface with 'ae-base' classes to display current weather conditions and forecast summaries.
6. Utilize 'ae-base' context managers to ensure proper handling of file operations during data storage and retrieval.
7. Add error handling to gracefully manage scenarios where the API request fails or the data cannot be parsed correctly.
8. Test the application thoroughly, ensuring that all features work as expected and data is accurately stored and retrieved.

Suggested Features:
- Display current temperature, humidity, wind speed, and other relevant weather metrics.
- Provide a 5-day weather forecast with daily high and low temperatures.
- Allow users to view cached weather data when offline.
- Enable users to set preferences for their favorite cities.
- Include a feature to notify users via email or SMS if severe weather conditions are predicted.