🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network, shell, obfuscation, and credential handling, but its newness and the limited history of the maintainer raise concerns about potential supply-chain attacks.

New package with limited maintainer history
Use of shell execution for command version checks needs further investigation

Per-check LLM notes

Network: No network calls detected, which is normal and expected.
Shell: Shell execution appears to be used for command version checks, indicating benign use but requires further investigation into the specific commands executed.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is new and the maintainer has limited history with PyPI, which could indicate potential risk.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://thalesgroup.github.io/agilab
Detailed PyPI description (2053 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 5.0

Partial type annotation coverage

142 type-annotated function signatures detected in source

✦ High Multiple Contributors 10.0

Active multi-contributor project

5 unique contributor(s) across 69 commits in ThalesGroup/agilab
Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

try: completed = subprocess.run( [command, "--version"], check=False
try: completed = subprocess.run(command, check=False, env=_child_uv_env()) except OSErro

✓ 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 ThalesGroup/agilab appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Package is very new: uploaded 3 day(s) ago
Author "Jean-Pierre Morard" 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 agi-apps

Create a weather forecasting mini-app using the Python package 'agi-apps'. This app should provide users with current weather conditions and forecasts for any city they input. The application will utilize 'agi-apps' for its core functionalities, such as data fetching and processing, which are essential for integrating external APIs and handling geographic data efficiently.

Step-by-Step Guide:
1. **Setup Project Environment**: Initialize a new Python project and install the necessary packages including 'agi-apps'.
2. **API Integration**: Use 'agi-apps' to integrate with a weather API (such as OpenWeatherMap). Configure the API key and set up functions to fetch current weather data and forecast information based on user inputs.
3. **User Interface**: Develop a simple command-line interface (CLI) where users can enter their city name and choose between viewing current weather conditions or a forecast. Implement error handling for invalid inputs.
4. **Data Display**: Utilize 'agi-apps' features to process and display the fetched data in a readable format. Include details like temperature, humidity, wind speed, and forecasted weather conditions for the next few days.
5. **Geolocation Features**: Enhance the app by allowing users to find their location automatically (using IP geolocation services) and display the local weather without needing to manually input a city name.
6. **Scheduling Updates**: Implement a feature that allows users to schedule regular updates of weather conditions and forecasts at specific intervals (e.g., every hour).
7. **Testing & Deployment**: Thoroughly test the application to ensure all features work correctly. Deploy the application to a cloud service (like AWS or Heroku) so it can be accessed via a web interface or CLI from anywhere.

Suggested Features:
- Interactive CLI for easy user interaction.
- Real-time weather updates.
- Detailed weather forecasts for up to 7 days.
- Geolocation support for automatic location detection.
- User-friendly data presentation.
- Scheduled updates for continuous monitoring of weather changes.

How 'agi-apps' is Utilized:
- For fetching and parsing weather data from external APIs.
- For handling geographic data to accurately determine and display location-specific information.
- For scheduling tasks to automate regular weather updates.
- For processing and formatting the retrieved data into a user-readable format.