alumnium

v0.20.0 suspicious
4.0
Medium Risk

Pave the way towards AI-powered test automation.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to potential shell execution risks and concerns over the maintainer's experience and package metadata quality.

  • Shell execution risk detected
  • Low quality metadata and maintainer information
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Shell execution is present but without specific commands or context, it's hard to assess intent; however, it could potentially be used for malicious purposes.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer appears new and the package lacks classifiers, indicating low effort or poor metadata quality.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1730 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 201 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 8 unique contributor(s) across 100 commits in alumnium-hq/alumnium
  • 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 2.0

Found 1 shell execution pattern(s)

  • in_path()), *args] return subprocess.run(command, check=check, capture_output=capture_output, text=te
✓ 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

Repository alumnium-hq/alumnium appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Sasha Koss, Alex Rodionov, Tatiana Shepeleva" 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 alumnium 
Create a fully-functional mini-application named 'TestBot' using the Python package 'alumnium', which specializes in AI-powered test automation. Your goal is to develop a tool that automates the testing process of web applications, ensuring they function correctly under various conditions. TestBot should be capable of generating test cases based on user inputs, executing these tests, and providing detailed reports on test outcomes.

Step-by-Step Guide:
1. **Setup**: Begin by setting up your development environment. Ensure you have Python installed along with the 'alumnium' package. Use pip to install 'alumnium' if it's not already installed.
2. **Design**: Design the architecture of your application. Consider how you will integrate 'alumnium' into your workflow. Plan for user interaction, test case generation, execution, and reporting.
3. **Integration**: Integrate 'alumnium' into your project. Utilize its capabilities to create intelligent test cases that adapt to different scenarios and environments.
4. **Development**: Start developing your application. Implement a user interface where users can input details about the web application they want to test (e.g., URLs, expected behaviors).
5. **Testing**: Use 'alumnium' to generate and execute test cases based on the provided information. Monitor the execution and collect data.
6. **Reporting**: After tests are executed, use 'alumnium' to analyze the results and generate comprehensive reports. These reports should include pass/fail statuses, detailed logs, screenshots, and recommendations for improvements.
7. **Enhancements**: Once the basic functionality is working, consider adding more features such as scheduling tests, integrating with CI/CD pipelines, or allowing users to save and reuse test cases.

Suggested Features:
- User-friendly GUI for easy input and control over the testing process.
- Ability to specify different types of tests (unit, integration, end-to-end).
- Automated generation of test cases based on provided specifications.
- Detailed logging and reporting of test results.
- Support for multiple browsers and devices.
- Integration with popular bug tracking systems for seamless issue reporting.

💬 Discussion Feed

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