AI Analysis
The package exhibits low risks in terms of network calls, shell execution, and obfuscation. However, its metadata suggests a lack of development effort and an untraceable repository, raising concerns about its authenticity.
- Low risk in network calls, shell execution, and obfuscation
- Suspicious metadata indicating potential low-effort creation and untraceable repository
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communications.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
- Metadata: The package shows signs of being newly created with low effort, and the repository is not found, raising suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (5338 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
16 type-annotated function signatures detected in source
Could not retrieve contributor data from GitHub
GitHub API error: 404
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 not found (deleted or private)
Repository not found (deleted or private)
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "Akindu Karunaratne" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based web application that allows users to execute Python code snippets dynamically within Azure Container Apps using the 'azure-dynamic-sessions-code-interpreter' package. This application will serve as a simple online Python IDE where users can write and run their Python scripts and receive immediate output results. The application should have the following core functionalities: 1. User Authentication: Implement a basic user authentication system where users can sign up and log in to the application. 2. Code Execution Interface: Provide a clean and user-friendly interface where authenticated users can input Python code snippets. 3. Dynamic Session Management: Utilize the 'azure-dynamic-sessions-code-interpreter' package to create, manage, and terminate dynamic code execution sessions on the Azure Container Apps platform. 4. Real-time Output Display: Show the output of the executed Python code in real-time within the web application. 5. Error Handling: Ensure robust error handling to provide meaningful feedback if the code fails to execute. 6. Code History: Allow users to view and re-execute their previous code snippets from a history tab. 7. Documentation: Include a brief documentation section explaining how to use the app effectively and any limitations or considerations for users. The 'azure-dynamic-sessions-code-interpreter' package will be used primarily for initiating and managing dynamic code interpretation sessions in Azure Container Apps. Users will be able to submit their Python code through the web interface, which will then be sent to Azure via the package's API for execution. The package will handle session creation, code interpretation, and session termination seamlessly behind the scenes, providing users with a responsive and reliable coding environment.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue