asta-code-execution

v0.1.5 safe
3.0
Low Risk

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🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across all categories except for metadata and shell usage, which suggest it might be poorly maintained or have legitimate but risky functionalities. However, there's no strong evidence of malicious intent.

  • Low network and credential risk
  • Potential misuse of shell commands
  • Incomplete metadata
Per-check LLM notes
  • Network: No network calls were detected, which is typical and not suspicious.
  • Shell: The use of shell execution to install packages and run code may indicate legitimate functionality but also poses a risk if not properly sanitized, suggesting potential for abuse.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low maintenance activity and lacks standard metadata, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ 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

  • 19 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 score 8.0

Found 4 shell execution pattern(s)

  • hon_bin.exists(): subprocess.run( [uv, "venv", str(venv_path), "--seed", "--p
  • f self._packages: subprocess.run( [uv, "pip", "install", "--python", str(pyth
  • xecution=={version}"] subprocess.run( [uv, "pip", "install", "--python", str(python_b
  • try: proc = subprocess.run( [python_bin, "-c", _SANDBOX_RUNNER],
✓ 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-code-execution 
Create a Python-based code execution sandbox application named 'CodeSandboxer' using the 'asta-code-execution' package. This application will allow users to securely execute Python code snippets within a controlled environment. The primary goal of CodeSandboxer is to provide developers and learners with a safe space to experiment with code without risking system integrity.

Step 1: Set up the Project Environment
- Initialize a new Python virtual environment and install the required packages, including 'asta-code-execution'.
- Create a basic directory structure for the project, including directories for source code, tests, and documentation.

Step 2: Design the User Interface
- Develop a simple command-line interface (CLI) for interacting with CodeSandboxer.
- Implement functionality to accept user input for code snippets and display output.

Step 3: Implement Core Functionality Using 'asta-code-execution'
- Utilize the 'asta-code-execution' package to safely execute user-provided Python code snippets.
- Ensure that the execution environment is isolated from the host system to prevent unauthorized access or damage.
- Handle exceptions gracefully and provide informative error messages to the user.

Step 4: Enhance with Additional Features
- Integrate a feature to save executed code snippets and their results to a local database.
- Allow users to load previous code snippets and continue working on them.
- Implement logging to track user interactions and execution outcomes for debugging purposes.

Step 5: Test and Validate
- Write unit tests to ensure the application functions as intended.
- Perform security testing to confirm that the sandbox environment effectively isolates code execution.
- Conduct user acceptance testing to gather feedback and refine the application.

Step 6: Document and Release
- Prepare comprehensive documentation detailing how to use CodeSandboxer, including setup instructions, usage examples, and troubleshooting tips.
- Publish the project on GitHub and share it with the developer community.

💬 Discussion Feed

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