backend.ai-webserver

v26.4.3 safe
3.0
Low Risk

Backend.AI WebUI Host

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SAFE

The package shows low risk across multiple categories including network, shell, obfuscation, and credential handling. The metadata risk is slightly elevated due to the maintainer having only one package, but this alone is insufficient to warrant suspicion.

  • No network calls detected
  • No shell execution patterns
  • No obfuscation or credential harvesting patterns
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of sensitive information.
  • Metadata: The maintainer has only one package, which could indicate a new or less active account, but there are no other red flags.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.backend.ai/
  • Detailed PyPI description (16775 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 9 unique contributor(s) across 100 commits in lablup/backend.ai
  • Active community — 5 or more distinct contributors

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository lablup/backend.ai appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Lablup Inc. and contributors" 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 backend.ai-webserver 
Create a fully-functional mini-application that serves as a user-friendly interface for managing and monitoring computational tasks on a cloud-based infrastructure using the Backend.AI WebUI Host package. This application will allow users to submit, manage, and track their jobs in real-time, providing them with valuable insights into resource usage and job status.

### Project Overview:
- **Application Name:** CloudTaskManager
- **Technology Stack:** Python (Backend.AI WebUI Host)
- **Target Audience:** Developers, Data Scientists, Researchers
- **Core Features:**
  - User Authentication and Authorization
  - Job Submission Form with Parameters Input
  - Real-Time Job Status Tracking
  - Resource Usage Monitoring (CPU, Memory, Disk)
  - Job History and Statistics

### Utilizing Backend.AI WebUI Host:
- Integrate Backend.AI WebUI Host to handle HTTP requests and responses, providing a robust web server foundation.
- Use Backend.AI's capabilities to manage and monitor computational resources, allowing users to interact with their jobs through a web interface.
- Implement job submission functionality that leverages Backend.AI's API to send jobs to the computational backend.
- Ensure real-time updates on job statuses by polling Backend.AI's API at regular intervals.
- Develop a dashboard to visualize resource usage and job statistics using Backend.AI's data.

### Step-by-Step Development Plan:
1. **Setup Environment**: Install Backend.AI WebUI Host and any necessary dependencies.
2. **Authentication Module**: Implement login and registration functionalities to ensure secure access.
3. **Job Submission Form**: Create a form where users can specify job parameters and submit them to the computational backend via Backend.AI.
4. **Real-Time Job Tracking**: Use WebSocket technology to provide live updates on job statuses.
5. **Resource Monitoring**: Display CPU, memory, and disk usage graphs based on data fetched from Backend.AI.
6. **Job History & Statistics**: Allow users to view past job details and analyze performance metrics.
7. **Testing & Deployment**: Thoroughly test the application and deploy it to a production environment.

### Additional Considerations:
- Ensure the application is responsive and works well across different devices.
- Provide clear documentation and user guides to help new users get started.
- Implement error handling and logging to ensure smooth operation and ease of debugging.

💬 Discussion Feed

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