appfx-storage

v0.1.1 suspicious
6.0
Medium Risk

Python helpers for Azure Storage Blob and Queue operations.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has no direct security risks like network calls or shell execution, but its metadata suggests potential malicious intent due to suspicious git repository activity and maintainer history.

  • Suspicious git repository activity
  • Unclear maintainer history
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or system manipulation.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of being potentially malicious due to suspicious git repository activity and maintainer history.

📦 Package Quality Overall: Medium (5.0/10)

✦ High Test Suite 9.0

Test suite present — 3 test file(s) found

  • Test runner config found: pyproject.toml
  • 3 test file(s) detected (e.g. test_async_helper_correctness.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4603 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 154 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 4 commits in Dongbumlee/appfx-storage
  • Single author with few commits — possibly a personal or throwaway project

🔬 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

Email domain looks legitimate: outlook.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Single contributor with only 4 commit(s) — possibly throwaway account
  • All 4 commits happened within 24 hours
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 appfx-storage 
Create a fully-functional mini-application called 'CloudBlobBackup' that leverages the 'appfx-storage' Python package to manage backups of local files to Azure Storage Blobs. This application should allow users to select directories on their local machine and schedule regular backups of these directories to Azure Storage Blobs. Additionally, the application should support restoring specific files from the cloud storage back to the local file system. Here’s a detailed breakdown of the application’s requirements:

1. **User Interface**: Design a simple, user-friendly interface using a Python GUI framework like PyQt or Tkinter.
2. **Directory Selection**: Allow users to browse and select one or more directories on their local machine for backup.
3. **Azure Storage Integration**: Use the 'appfx-storage' package to interact with Azure Storage Blobs. Ensure you handle authentication securely using Azure AD credentials or SAS tokens.
4. **Backup Scheduling**: Implement a scheduler within the application that allows users to set up recurring backups at specified intervals (e.g., daily, weekly).
5. **File Upload/Download**: Utilize 'appfx-storage' to upload selected files to Azure Storage Blobs and download them back when needed.
6. **Logging**: Maintain a log file of all backup activities, including successes and failures.
7. **Error Handling**: Implement robust error handling to deal with issues such as network connectivity problems or storage access errors.
8. **Security**: Ensure that sensitive information like credentials are stored securely and not hard-coded in the application.
9. **Documentation**: Provide clear documentation on how to install dependencies, configure the application, and use it effectively.

By completing this project, you will gain hands-on experience with Python GUI development, scheduling tasks, and utilizing cloud storage services via a Python package.

💬 Discussion Feed

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