🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits minimal direct security risks but raises concerns due to low-effort signs and lack of community engagement, which may indicate potential supply-chain risks.

Metadata risk score of 6 out of 10
Lack of community engagement

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows several low-effort signs and lack of community engagement, raising concerns about its legitimacy.

🔬 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

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 8.0

4 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)
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 PyHeal

Create a Python-based mini-application called 'ErrorGuard' that leverages the PyHeal package to provide robust error handling and self-healing capabilities for executing user-defined Python scripts. ErrorGuard should serve as a safeguard against common runtime errors, ensuring that even if parts of the script fail, the overall execution can recover gracefully. Here are the key steps and features your application should include:

1. **User Interface**: Develop a simple command-line interface (CLI) where users can input their Python code snippets or scripts.
2. **Script Execution**: Implement a feature within ErrorGuard that takes the user's input code, wraps it in PyHeal’s safe execution blocks, and runs it.
3. **Error Handling & Recovery**: Utilize PyHeal to automatically detect and handle exceptions that occur during script execution. Ensure that any caught errors trigger a recovery mechanism provided by PyHeal, allowing the script to continue running from the point of failure or restart sections that failed.
4. **Logging & Reporting**: Integrate logging to capture all execution details, including successful operations and any errors encountered. Provide a summary report at the end of each run detailing what worked and what didn't, along with suggestions on how to prevent future issues.
5. **Interactive Mode**: Offer an interactive mode where users can experiment with different error scenarios and see how PyHeal's self-healing mechanisms respond.
6. **Configuration Options**: Allow users to configure settings such as retry limits, types of exceptions to catch, and logging verbosity through command-line arguments or a configuration file.
7. **Documentation**: Write comprehensive documentation explaining how to use ErrorGuard effectively, highlighting best practices for writing resilient Python code and leveraging PyHeal’s features.

Your goal is to demonstrate how PyHeal can enhance the reliability and maintainability of Python applications by providing automated error recovery and safe execution contexts.