app_build_suite

v2.1.2 suspicious
4.0
Medium Risk

An app build suite for GiantSwarm app platform

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a low risk score due to minimal network, shell, obfuscation, and credential risks. However, concerns about the maintainer's history make it suspicious.

  • Maintainer history raises suspicion
  • Low risk in technical aspects
Per-check LLM notes
  • Network: The network call is likely used for downloading an icon file, which is common for build tools needing resources.
  • Shell: No shell execution patterns detected, indicating low risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: Low risk due to lack of suspicious indicators, but concerns about maintainer history suggest potential low effort or new account.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (9145 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 74 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: return urllib.request.urlretrieve(icon_path, tmp_file_path)[0] # nosec ex
✓ 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

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 app_build_suite 
Create a fully functional mini-app using the 'app_build_suite' Python package, which is tailored for the GiantSwarm app platform. Your task is to develop a user-friendly dashboard that monitors the health and performance of various services deployed on the GiantSwarm platform. This dashboard will serve as a central point for administrators to gain insights into their applications' status, manage configurations, and troubleshoot issues efficiently.

### Project Scope:
- **Health Monitoring:** Integrate real-time monitoring capabilities to track the status of different services (e.g., uptime, response time, error rates).
- **Configuration Management:** Allow users to configure settings directly from the dashboard, such as adjusting thresholds for alerts or setting up new monitoring checks.
- **Alerts & Notifications:** Implement a system that sends out notifications via email/SMS when certain conditions are met (e.g., high CPU usage, low disk space).
- **User Interface:** Design a clean, intuitive UI that presents data clearly and makes it easy for users to interact with the app.

### Steps to Build the Application:
1. **Setup Environment:** Begin by installing the necessary packages including 'app_build_suite'. Ensure your development environment is set up correctly for working with GiantSwarm.
2. **Data Collection:** Use the 'app_build_suite' package to collect data about the services running on the GiantSwarm platform. This includes metrics like uptime, response times, and error logs.
3. **Dashboard Development:** Develop the front-end of your application using any framework you prefer (e.g., Flask, Django). The dashboard should display collected data in real-time and allow users to perform actions like configuring alerts.
4. **Backend Logic:** Implement the backend logic using Python. Utilize 'app_build_suite' functions to interact with the GiantSwarm API for retrieving service statuses and sending commands.
5. **Testing & Deployment:** Thoroughly test your application to ensure all features work as expected. Deploy the app using the deployment tools provided by GiantSwarm, leveraging 'app_build_suite' for streamlined deployment processes.

### Utilizing 'app_build_suite':
- **Initialization:** Start by initializing your project with 'app_build_suite', setting up the required configurations for connecting to the GiantSwarm platform.
- **Service Interaction:** Use 'app_build_suite' methods to query service information, retrieve metrics, and send commands to services.
- **Deployment & Maintenance:** Leverage 'app_build_suite' for deploying your application and managing its lifecycle, ensuring it runs smoothly on the GiantSwarm platform.

This project aims to showcase the power and flexibility of 'app_build_suite' while providing a valuable tool for GiantSwarm users.

💬 Discussion Feed

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