AI Analysis
Final verdict: SAFE
The package appears to be designed for internal use, focusing on metadata collection within a specific data platform setup. While there are some concerns regarding metadata handling, there is no concrete evidence of malicious intent or activity.
- Suspicious non-HTTPS link and missing repository
- No network calls, shell execution, obfuscation, or credential harvesting detected
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
- Shell: No shell execution detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: Suspicious non-HTTPS link and missing repository raise concerns, but no clear evidence of malicious intent.
Package Quality Overall: Low (2.0/10)
○ 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 (25596 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
○ Low
Multiple Contributors
1.0
Could not retrieve contributor data from GitHub
GitHub API error: 404
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
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://datahub-gms.internal:8080
Git Repository History
score 3.0
Repository not found (deleted or private)
Repository not found (deleted or private)
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "jangwansik" 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 aileron-meta-collector
Your task is to develop a mini-application that automates the collection of data lineage metadata using the 'aileron-meta-collector' package. This tool leverages SQLAlchemy and boto3 event hooks to automatically capture lineage information from various data sources and store it in a centralized DataHub repository. Your application will serve as a proof-of-concept for how organizations can streamline their data governance processes. ### Project Scope: 1. **Data Source Integration**: Integrate your application with at least two different data sources, such as a PostgreSQL database and an S3 bucket, to demonstrate the versatility of the 'aileron-meta-collector'. 2. **Metadata Collection**: Automatically collect metadata about the data flow, including data transformations and movements between the integrated data sources. 3. **Centralized Storage**: Use the DataHub platform to store and manage the collected metadata, ensuring that the lineage information is easily accessible and searchable. 4. **User Interface**: Develop a simple web interface using Flask or Django to visualize the collected lineage data. Users should be able to query the lineage information based on specific criteria (e.g., data source, transformation type). 5. **Security and Compliance**: Implement basic security measures to ensure that only authorized users can access the lineage information. Additionally, comply with GDPR or other relevant data protection regulations by anonymizing personal data where necessary. 6. **Documentation and Testing**: Provide comprehensive documentation for setting up and using the application. Include unit tests for critical components of the application to ensure reliability and robustness. ### Utilization of 'aileron-meta-collector': - **Integration with SQLAlchemy**: Use the package's integration with SQLAlchemy to hook into database events (e.g., table creation, data insertion) and capture lineage metadata accordingly. - **AWS S3 Support**: Leverage the package's support for boto3 to monitor changes in AWS S3 buckets and record these activities in the lineage metadata. - **Custom Event Handling**: Extend the functionality of 'aileron-meta-collector' by adding custom event handlers to capture additional types of data movement or transformation not covered by default. - **DataHub API Interaction**: Utilize the package's capabilities to interact with the DataHub API, ensuring that all captured metadata is properly formatted and stored in the DataHub repository. ### Deliverables: - A fully functional mini-application that integrates with at least two data sources and captures lineage metadata. - A user-friendly web interface for visualizing and querying lineage information. - Comprehensive documentation and unit tests for the application. - A demonstration video showcasing the application's key features and functionality.