apache-airflow-providers-box

v2.0.5 safe
4.0
Medium Risk

Box.com provider for Apache Airflow.

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activities such as network risks, shell risks, obfuscation, or credential theft. However, the metadata risk due to low repository activity and sparse maintainer profile suggests some caution is warranted.

  • No network or shell execution risks detected.
  • Repository and maintainer profiles suggest potential lack of maintenance.
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 local privilege escalation.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's low activity and the maintainer's sparse profile raise concerns but do not definitively indicate malicious intent.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: conftest.py
  • 7 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (704 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

  • 55 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 50 commits in graduatecollege/apache-airflow-providers-box
  • Small but multi-author team (3–4 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

Email domain looks legitimate: illinois.edu>

✓ 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 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 apache-airflow-providers-box 
Create a mini-application using Apache Airflow that automates the process of uploading files from a local directory to a Box.com account. This application will demonstrate the integration capabilities of the 'apache-airflow-providers-box' package and provide a practical example of managing workflows involving cloud storage services.

### Project Overview:
- **Name:** FileUploaderToBox
- **Goal:** Automate the upload of files from a specified local directory to a designated folder within a Box.com account.
- **Features:**
  - Schedule file uploads at regular intervals (e.g., daily).
  - Handle file metadata (such as names, descriptions, and tags).
  - Implement error handling for failed uploads.
  - Provide a log of uploaded files and any errors encountered.
- **Technologies Used:**
  - Python
  - Apache Airflow
  - Box API via 'apache-airflow-providers-box'

### Steps to Build the Application:
1. **Setup Environment:**
   - Install necessary Python packages including 'apache-airflow', 'apache-airflow-providers-box', and other dependencies.
   - Configure Airflow to connect with your Box.com account by setting up the appropriate environment variables or configuration files.
2. **Define Operators:**
   - Use the 'BoxOperator' provided by 'apache-airflow-providers-box' to interact with the Box API.
   - Create custom operators if needed to handle specific tasks such as listing files, checking for file existence, etc.
3. **Create DAGs:**
   - Design Directed Acyclic Graphs (DAGs) to represent the workflow of your application.
   - Schedule these DAGs to run at predefined intervals using Airflow's scheduling capabilities.
4. **Implement Logic for File Uploads:**
   - Write logic to read files from a specified local directory.
   - Use the BoxOperator to upload these files to a designated folder in your Box account.
5. **Error Handling and Logging:**
   - Implement robust error handling to manage cases where uploads fail.
   - Log all actions taken during the upload process, including successes and failures, to a central location for monitoring and troubleshooting.
6. **Testing:**
   - Test the application thoroughly to ensure it works as expected under various conditions.
   - Validate that files are correctly uploaded and that logs accurately reflect the state of each upload attempt.
7. **Deployment:**
   - Deploy the application to a production-like environment.
   - Monitor its performance and adjust as necessary based on real-world usage.

This project will not only showcase the power of Apache Airflow in orchestrating complex workflows but also highlight how easily it can integrate with external services like Box.com through its provider system.

💬 Discussion Feed

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