asta-sandbox

v0.1.2 safe
3.0
Low Risk

Shared code execution sandbox abstractions for Asta projects

🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no detected network calls, shell executions, obfuscations, or credential risks. The metadata risk is slightly elevated due to low-effort indicators and lack of a GitHub repository, but this does not strongly suggest malicious activity.

  • No network calls or shell executions detected
  • Lack of GitHub repository noted
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interactions.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows some low-effort indicators and lacks a GitHub repository, but there's no direct evidence of malice.

📦 Package Quality Overall: Low (3.8/10)

◈ 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 (8999 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

  • 53 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Allen Institute for Artificial Intelligence" 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 asta-sandbox 
Create a Python-based educational tool called 'CodePlayground' that leverages the 'asta-sandbox' package to provide a secure environment for users to experiment with different programming languages and snippets of code. This application will allow users to input code, select a language, and execute it within a sandboxed environment to see the output without risking their local machine's security. Here are the key features and steps to develop this application:

1. **Setup Environment**: Begin by setting up a Python virtual environment and installing the 'asta-sandbox' package along with other necessary dependencies like Flask for web framework and Pygments for syntax highlighting.
2. **Design User Interface**: Develop a simple yet intuitive web interface using HTML, CSS, and JavaScript. Ensure the design is responsive and user-friendly.
3. **Backend Development**: Utilize Flask to create the backend server. Implement routes for handling code submission, language selection, and code execution requests.
4. **Sandbox Execution**: Integrate 'asta-sandbox' to safely execute user-submitted code within isolated containers. Configure the sandbox to support multiple programming languages such as Python, JavaScript, and Bash.
5. **Output Display**: Capture the output from the executed code and display it back to the user in a clean manner. Handle errors gracefully and provide meaningful error messages.
6. **Syntax Highlighting**: Use Pygments to highlight the code syntax based on the selected language, enhancing readability and user experience.
7. **Testing & Security**: Rigorously test the application to ensure it works as expected and is secure against common vulnerabilities like code injection. Verify that the sandbox effectively isolates each execution.
8. **Deployment**: Once development is complete, deploy the application on a platform like Heroku or AWS so it can be accessed over the internet.

This project aims to provide a safe and engaging way for learners and developers to practice coding skills without the risk of harming their systems.

💬 Discussion Feed

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