🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks but has some suspicious metadata indicators. The absence of a GitHub repository and the presence of a non-HTTPS link raise concerns about its legitimacy and maintenance.

Suspicious non-HTTPS link in metadata
Lack of a GitHub repository

Per-check LLM notes

Network: The network calls are likely for legitimate purposes, such as API interactions or updates, but could potentially be used for data exfiltration if misused.
Shell: No shell execution patterns detected, which is expected and safe.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Suspicious non-HTTPS link and lack of GitHub repository suggest potential risks, but limited maintainer history and no typosquatting indicate it may not be actively malicious.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

s + 1): request = urllib.request.Request(url, data=body, method=method) request.a
try: with urllib.request.urlopen(request) as response: return res

✓ 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 score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:21212

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Aerol AI" 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 aerolvm-sdk

Create a Python-based utility named 'MicroVM Runner' that leverages the 'aerolvm-sdk' package to manage and execute lightweight virtual machines (MicroVMs) within a secure sandbox environment provided by Aerol.ai. This tool will allow users to upload, run, and monitor various applications in isolated MicroVMs, ensuring safety and resource efficiency. Here's a step-by-step guide on how to develop this utility:

1. **Setup Project Environment**: Begin by setting up a Python virtual environment and installing the 'aerolvm-sdk'. Additionally, include any other necessary libraries such as requests for HTTP requests if needed.
2. **User Interface Design**: Design a simple command-line interface (CLI) or a basic web interface using Flask for users to interact with the MicroVM Runner. The interface should allow users to select from predefined application templates or upload their own code to run in a MicroVM.
3. **MicroVM Management Functions**: Implement functions to create, start, stop, and delete MicroVM instances through the 'aerolvm-sdk'. Ensure these functions handle authentication with Aerol.ai's API and manage resources efficiently.
4. **Application Deployment**: Develop a feature that allows users to deploy applications into the running MicroVMs. This could involve uploading source code or pre-built binaries, configuring runtime environments, and setting up necessary dependencies.
5. **Monitoring and Logging**: Integrate monitoring capabilities that allow users to view logs and status updates of the running applications in real-time. Use the SDK to fetch and display relevant information about the MicroVM's performance and health.
6. **Security Enhancements**: Since security is paramount when dealing with virtualized environments, ensure your utility includes features to securely manage access, restrict permissions, and log all activities for auditing purposes.
7. **Testing and Documentation**: Thoroughly test each component of the utility to ensure reliability and robustness. Provide comprehensive documentation detailing setup instructions, usage examples, and troubleshooting tips for both developers and end-users.

Suggested Features:
- Support for multiple programming languages and frameworks.
- Automatic scaling based on load.
- Integration with CI/CD pipelines for seamless deployment processes.
- Detailed analytics and reporting tools.
- Advanced security measures like encryption and multi-factor authentication.