AI Analysis
The package exhibits minimal direct security risks, but the metadata suggests potential issues with maintenance and authorship effort.
- Low network, shell, obfuscation, and credential risks
- Metadata risk due to low maintenance and authorship effort
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network functionality.
- Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, suggesting legitimate use without security compromise.
- Metadata: The package shows low maintenance and authorship effort, raising some suspicion but not definitive evidence of malice.
Package Quality Overall: Low (4.8/10)
Partial test coverage signals detected
1 test file(s) detected (e.g. test_runner.py)
Some documentation present
Detailed PyPI description (19232 chars)
Some contribution signals present
Governance file: security.py
Partial type annotation coverage
66 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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
Your task is to create a fully-functional mini-app that leverages the 'aiel-runtime' Python package to manage and execute user-defined scripts within a controlled environment. This app will serve as a sandbox where users can upload their Python scripts and have them run safely and efficiently without affecting the host system. ### Project Overview: - **Name:** ScriptSandbox - **Purpose:** To provide a secure, isolated environment for executing user-provided Python scripts. - **Features:** - User script upload via web interface or API. - Secure execution of uploaded scripts using 'aiel-runtime'. - Real-time output logging and error handling. - Optional feature: support for script versioning. ### Detailed Steps: 1. **Setup Environment:** Create a virtual environment and install necessary packages including 'aiel-runtime', Flask (for web framework), and any other dependencies. 2. **User Interface Development:** Develop a simple web interface where users can upload their Python scripts. Ensure there is also an option to specify a unique identifier for each script. 3. **Script Execution:** Utilize 'aiel-runtime' to load and execute the uploaded scripts in a sandboxed environment. Handle any exceptions or errors gracefully and log them for review. 4. **Output Management:** Capture the standard output and errors from the executed scripts and display them back to the user in real-time through the web interface. 5. **Security Measures:** Implement basic security checks before executing any script to prevent malicious code execution. Use 'aiel-runtime' functionalities to further enhance security. 6. **Optional - Version Control:** Allow users to save different versions of their scripts and retrieve previous versions if needed. 7. **Testing & Deployment:** Test the application thoroughly and deploy it on a cloud service like Heroku or AWS. ### How 'aiel-runtime' is Used: - **Loading Scripts:** Use 'aiel-runtime' to load user scripts into memory without directly executing them until explicitly instructed. - **Execution Context:** Set up an execution context that isolates the script from the main application environment, ensuring no harmful actions can affect the host system. - **Monitoring:** Monitor the execution process for any anomalies or failures, logging all relevant data for future analysis and troubleshooting. - **Resource Management:** Manage resources allocated to each script execution carefully to avoid overloading the system. This project aims to showcase the capabilities of 'aiel-runtime' while providing a practical solution for developers who need a safe way to test and execute Python code snippets.
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