AI Analysis
The package shows minimal risk indicators with no network calls, shell executions, or obfuscation techniques observed. The metadata suggests a potential new maintainer, but there are no clear signs of malicious intent or supply-chain attack.
- No network calls detected
- Single package from maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
- 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 may indicate a new or less active account, but no other red flags were raised.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Limited contributor diversity
1 unique contributor(s) across 100 commits in jvalenzuela/atformSingle author but highly active (100 commits)
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com
All external links appear legitimate
Repository jvalenzuela/atform appears legitimate
1 maintainer concern(s) found
Author "Jason Valenzuela" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a user-friendly web-based acceptance testing tool using Flask as the backend framework and Bootstrap for frontend styling. This tool will allow users to generate acceptance test procedures forms for various software applications based on predefined templates provided by the 'atform' package. The application should include the following features: 1. User Authentication: Implement registration, login, and logout functionalities to ensure only registered users can create and manage their test procedures. 2. Test Procedure Form Generation: Utilize the 'atform' package to dynamically generate acceptance test procedure forms. Users should be able to select from a variety of pre-defined templates (e.g., UI testing, API testing, database testing) and customize these templates by adding or removing specific test cases. 3. Form Customization: Allow users to add custom fields to the forms if they require additional information not covered by the default templates. 4. Submission and Storage: After completing a form, users should be able to submit it. All submitted forms should be stored securely in a database for future reference and retrieval. 5. Reporting: Provide users with the ability to generate reports based on the completed test procedure forms. These reports should summarize key findings and highlight any issues encountered during testing. 6. Integration Testing: Ensure the application works seamlessly with the 'atform' package by thoroughly testing the form generation process and ensuring all data is accurately stored and retrieved. 7. User Interface: Design a clean, intuitive interface using Bootstrap to enhance user experience. The interface should be responsive, ensuring it looks good on both desktop and mobile devices. 8. Documentation: Write comprehensive documentation detailing how to use the application, including setup instructions, usage guides, and troubleshooting tips. Your task is to design and implement this application, paying special attention to how you integrate the 'atform' package to leverage its capabilities for generating and customizing acceptance test procedure forms.
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