auctor-monty

v0.0.18 suspicious
6.0
Medium Risk

Auctor fork of the Monty sandboxed Python interpreter bindings

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits unusually high metadata risk due to a lack of maintainer activity and details, which raises concerns about its legitimacy.

  • High metadata risk due to a newly created repository and inactive maintainer
  • Lack of detailed author information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell executions detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
  • Metadata: The repository is newly created with no activity, the maintainer has a new or inactive account, and there's no author information provided.

📦 Package Quality Overall: Low (4.8/10)

◈ 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 (2836 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 14 unique contributor(s) across 100 commits in tjbai/monty
  • Active community — 5 or more distinct contributors

🔬 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 score 5.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-06-02T16:19:43Z)

  • Repository created very recently: 5 day(s) ago (2026-06-02T16:19:43Z)
  • Repository has zero stars and zero forks
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with auctor-monty 
Create a secure Python code execution environment using the 'auctor-monty' package. Your task is to develop a web-based mini-application where users can submit Python code snippets for execution in a sandboxed environment. This application should ensure that the executed code does not have access to the underlying system resources, preventing any potential security threats. Here’s a detailed breakdown of the project requirements:

1. **Setup Environment**: Install necessary packages including Flask for the web framework and 'auctor-monty' for sandboxing Python code.
2. **Web Interface**: Develop a simple web interface using HTML/CSS/JavaScript where users can input their Python code and execute it.
3. **Sandbox Execution**: Utilize 'auctor-monty' to safely execute user-submitted code within a sandboxed environment. Ensure that the sandbox limits the execution time and memory usage to prevent abuse.
4. **Output Display**: After executing the code, display the output back to the user on the web interface.
5. **Error Handling**: Implement robust error handling to catch any exceptions during code execution and provide meaningful error messages to the user.
6. **Security Features**: Include mechanisms to prevent common security vulnerabilities such as code injection attacks. Use 'auctor-monty' features to restrict file system access and network communication from the sandboxed environment.
7. **Testing**: Write tests to ensure that your application works correctly under various scenarios, including valid code submissions and malicious code attempts.
8. **Documentation**: Provide clear documentation explaining how to install and run the application, along with examples of how to use the sandboxed execution feature.

This project aims to showcase the capabilities of 'auctor-monty' in creating safe, isolated environments for executing untrusted Python code. By following these steps, you will create a valuable tool for developers and educators who want to demonstrate Python code execution without risking system security.

💬 Discussion Feed

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