backend.ai-install

v26.4.3 safe
4.0
Medium Risk

Backend.AI Installer

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with minimal risks identified. The potential modification of the /etc/hosts file warrants caution but does not conclusively indicate malicious intent.

  • Potential risk of modifying /etc/hosts file
  • No shell execution or obfuscation detected
Per-check LLM notes
  • Network: The network call patterns indicate legitimate use of aiohttp for HTTP requests, which is common in many applications and does not inherently suggest malicious behavior.
  • Shell: No shell execution patterns were detected, indicating there is no evidence of the package executing arbitrary commands.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: Potential risk of modifying /etc/hosts file, which could be used for redirection or DNS spoofing attacks.
  • Metadata: The maintainer has only one package, suggesting it may be a new or less active account.

📦 Package Quality Overall: Medium (5.4/10)

○ 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/
  • Brief PyPI description (703 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 190 type-annotated function signatures detected in source
✦ 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 score 6.0

Found 4 network call pattern(s)

  • ion", stdout) async with aiohttp.ClientSession(connector=connector.connector) as sess: async with s
  • ) try: async with aiohttp.ClientSession(connector=connector.connector) as sess: async wi
  • TCPConnector() async with aiohttp.ClientSession(connector=connector) as s: async with s.request(meth
  • r(socket_path) async with aiohttp.ClientSession(connector=connector) as s: async with s.request(meth
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 10.0

Found 4 credential access pattern(s)

  • name="Add host aliases at /etc/hosts", path="/etc/hosts", content=etc_ho
  • etc/hosts", path="/etc/hosts", content=etc_hosts_content, marker
  • ame="Remove host aliases from /etc/hosts", path="/etc/hosts", marker=self.et
  • etc/hosts", path="/etc/hosts", marker=self.etc_hosts_block_marker,
✓ 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-install 
Create a Python-based mini-application named 'AI Lab Setup Assistant' which leverages the Backend.AI Installer package to streamline the process of setting up a local AI development environment. This application should provide users with a simple and interactive way to install and configure all necessary components for AI research and development on their machine. The main functionalities of the 'AI Lab Setup Assistant' include:

1. **Environment Setup Wizard**: Guide users through the installation of Backend.AI server and client components, including Docker and any required dependencies.
2. **Configuration Manager**: Allow users to customize their setup by selecting specific AI frameworks (e.g., TensorFlow, PyTorch) and other tools they need for their projects.
3. **Status Checker**: Provide real-time feedback during the installation process and post-installation status checks to ensure everything is functioning correctly.
4. **Documentation Generator**: Automatically generate a user manual detailing the installed components, configurations, and basic usage instructions.
5. **Troubleshooting Tool**: Offer quick access to common issues and solutions related to Backend.AI installation and configuration.

The application should utilize the Backend.AI Installer package to handle the heavy lifting of downloading, installing, and configuring Backend.AI components. Users should be able to run the application from the command line or via a graphical interface (optional), making it accessible to both developers and non-technical users. Additionally, the application should be designed with modularity in mind, allowing for easy updates and extensions as new AI tools become available.

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