AI Analysis
Final verdict: SUSPICIOUS
The package shows low risks in network, shell, obfuscation, and credential aspects but has moderate metadata risk due to low activity and lack of detailed information, which raises suspicion.
- Low network, shell, obfuscation, and credential risks
- Moderate metadata risk due to low activity and insufficient details
Per-check LLM notes
- Network: Network calls are expected for deployment packages to communicate with Docker or other services during setup.
- Shell: No shell execution patterns were detected, indicating low risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The low activity and lack of detailed metadata suggest potential low effort or inactivity, raising some suspicion.
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
st:{port}" async with httpx.AsyncClient(base_url=base_url, timeout=60) as client: for _
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 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "Agentiix" 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 agentix-deployment-docker
Create a fully-functional mini-application that automates the deployment of a simple web server using Docker, leveraging the 'agentix-deployment-docker' package. Your application should allow users to specify the type of web server (e.g., Nginx, Apache), the version, and any additional configurations required for the container. The application will then use the 'agentix-deployment-docker' package to build, tag, and push the Docker image to a specified Docker registry, as well as deploy it to a chosen Kubernetes cluster. Key Features: 1. User Interface: A simple command-line interface (CLI) or a basic web UI for user interaction. 2. Configuration Management: Allow users to input specific configuration files for their web server (e.g., Nginx.conf). 3. Deployment Automation: Automatically handle Docker image building, tagging, pushing, and deployment to Kubernetes. 4. Logging & Monitoring: Implement basic logging and monitoring features to track the status of deployments. 5. Rollback Mechanism: Provide a feature to rollback to a previous version of the deployed application if something goes wrong during the deployment process. How to Utilize 'agentix-deployment-docker': - Use the package's functions to manage Docker images and containers efficiently. - Leverage its capabilities to streamline the deployment process onto Kubernetes clusters. - Integrate its logging and monitoring functionalities into your application for real-time feedback on deployments. Your task is to design and implement this mini-application from scratch, ensuring it is modular, maintainable, and easy to extend.