🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks due to its ability to execute shell commands and has suspicious metadata. However, there is no evidence of malicious intent or credential harvesting.

High shell risk
Suspicious metadata

Per-check LLM notes

Network: Network calls are common in cloud-related packages and may be necessary for the package's functionality.
Shell: Executing shell commands can pose a risk if not properly sanitized or controlled, especially if it allows for arbitrary command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Suspicious non-HTTPS links and lack of maintainer information suggest potential risks.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

try: async with httpx.AsyncClient(timeout=self.timeout) as client: response =

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

") try: process = subprocess.Popen( [node, str(bridge)], cwd=str(runtim
derr() -> None: process = subprocess.Popen( [ sys.executable, "-c",

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 6.0

Found 3 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:8000/dashboard/today
Non-HTTPS external link: http://127.0.0.1:8000/tasks/create
Non-HTTPS external link: http://127.0.0.1:8000/anything

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

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 agentify-cloud

Your task is to create a mini-application named 'CloudAgentDashboard' using the Python package 'agentify-cloud'. This application will serve as a dashboard for managing various cloud-based resources through a local Pi AgentSession. Here’s a step-by-step guide on what your application should do:

1. **Setup**: Begin by installing the necessary packages including 'agentify-cloud', FastAPI, and any other dependencies required for the project.
2. **Initialization**: Initialize the application by setting up a FastAPI server. Use 'agentify-cloud' to configure a local Pi AgentSession that acts as the gateway to manage cloud resources.
3. **Resource Management**: Implement endpoints for adding, removing, and updating cloud resources. These could include virtual machines, storage volumes, and network interfaces. Ensure that each operation is logged and tracked through the local Pi AgentSession.
4. **Monitoring**: Develop monitoring capabilities within the dashboard. Users should be able to view real-time status updates of their resources. Integrate 'agentify-cloud' to fetch and display this information efficiently.
5. **Security**: Secure the application by implementing authentication and authorization mechanisms. Ensure that only authorized users can perform resource management actions.
6. **Documentation**: Provide comprehensive documentation for the application, detailing how to install it, set it up, and use its features effectively.
7. **Testing**: Write tests to ensure that all functionalities work as expected. Include unit tests for individual functions and integration tests for the overall workflow.
8. **Deployment**: Prepare the application for deployment. Consider deploying it on a cloud platform like AWS or GCP, leveraging the capabilities provided by 'agentify-cloud'.

Suggested Features:
- User-friendly interface for managing cloud resources.
- Detailed logs and audit trails for all operations performed on resources.
- Real-time notifications for critical events related to cloud resources.
- Scalability options to handle increasing numbers of users and resources.

How 'agentify-cloud' is Utilized:
- For setting up the FastAPI server and configuring the local Pi AgentSession.
- To manage interactions between the application and cloud resources.
- To optimize performance by utilizing the gateway functionality provided by 'agentify-cloud'.
- For securing communications and data integrity during transactions.