AI Analysis
The package is considered safe as it does not exhibit any significant signs of malicious activity. The metadata risk is minor, mainly due to incomplete author information.
- Low obfuscation risk
- No detected credential harvesting
- Minor metadata risk due to incomplete author details
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
- Metadata: The package shows some red flags due to the author's information being incomplete, but no other suspicious elements were found.
Package Quality Overall: Medium (6.2/10)
Test suite present — 3 test file(s) found
Test runner config found: pyproject.toml3 test file(s) detected (e.g. __init__.py)
Some documentation present
Documentation URL: "documentation" -> https://github.com/terminaloutcomes/appinspect-submit/blob/mDetailed PyPI description (802 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
14 type-annotated function signatures detected in source
Limited contributor diversity
2 unique contributor(s) across 100 commits in terminaloutcomes/appinspect-submitTwo distinct contributors found
Heuristic Checks
Found 2 network call pattern(s)
try: response = requests.get(url=url, headers=headers, auth=auth) response.ra") response = requests.post( url=f"{APPINSPECT_BASE_URL}/v1/app/vali
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: terminaloutcomes.com>
All external links appear legitimate
Repository terminaloutcomes/appinspect-submit appears legitimate
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based mini-application named 'AppInspectHelper' that streamlines the process of submitting applications to Splunk AppInspect using the 'appinspect-submit' package. This tool will not only submit apps but also provide feedback on the submission status and handle any errors gracefully. Step-by-Step Requirements: 1. Integrate the 'appinspect-submit' package into your project. 2. Design a user-friendly command-line interface (CLI) that allows users to specify their app's path and other necessary details. 3. Implement error handling to manage common issues such as invalid paths, network failures, and API rate limits. 4. Display real-time progress during the submission process and notify the user when the submission is complete. 5. Provide detailed feedback on the submission result, including any errors or warnings returned by Splunk AppInspect. 6. Optionally, allow users to schedule regular submissions for continuous integration purposes. 7. Ensure the application logs all actions and results for auditing and debugging purposes. Suggested Features: - Support for multiple app submission formats recognized by Splunk AppInspect. - Integration with configuration files for storing default settings and credentials securely. - An option to automatically retry failed submissions after a specified interval. - A feature to compare previous submission results against new ones to highlight changes and improvements. - A help menu that provides usage instructions and examples. How 'appinspect-submit' is Utilized: - Use 'appinspect-submit' to handle the actual submission process to Splunk AppInspect. - Leverage its capabilities to parse and interpret the response from Splunk AppInspect, providing actionable insights to the user. - Employ its features to validate the app before submission, ensuring it meets the required standards.
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