aws-resource-validator-invoicing

v2.0.3 suspicious
4.0
Medium Risk

Pydantic v2 models for AWS invoicing, shipped as a PEP 420 namespace extension of aws-resource-validator.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network usage, shell execution, obfuscation, and credential handling. However, the incomplete metadata and the maintainer's limited presence on the platform raise some concerns about potential supply-chain risks.

  • Missing maintainer's author name
  • Single package by maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package focused on local validation and invoicing tasks.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands that could pose a risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The maintainer's author name is missing and they appear to have only one package, which might indicate a less experienced or potentially suspicious account.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

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

Some documentation present

  • Brief PyPI description (306 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 75 commits in CoreOxide/aws_resource_validator
  • 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository CoreOxide/aws_resource_validator appears legitimate

⚠ 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 aws-resource-validator-invoicing 
Create a Python-based mini-application that helps AWS users manage their invoicing data more efficiently using the 'aws-resource-validator-invoicing' package. This tool will parse and validate AWS invoicing data against predefined Pydantic models, ensuring that the data adheres to specific schemas. The application should also provide functionalities to visualize the parsed data and generate summary reports.

Step-by-Step Instructions:
1. Set up a virtual environment and install the required packages, including 'aws-resource-validator-invoicing'.
2. Utilize the Pydantic models from 'aws-resource-validator-invoicing' to define the structure of AWS invoicing data.
3. Implement a parser that reads raw invoicing data from a CSV file and validates it against the defined models.
4. Develop a feature to visualize the validated data using matplotlib or any other plotting library of your choice.
5. Create a report generator that outputs a summary of the invoicing data, including total costs, average monthly expenses, and any anomalies detected during validation.
6. Add error handling to manage invalid data gracefully and provide meaningful feedback to the user.
7. Ensure the application is modular and easy to extend for future enhancements.

Suggested Features:
- Interactive command-line interface for easy data input and output.
- Support for multiple data sources (CSV, JSON, etc.).
- Integration with AWS SDKs for fetching live invoicing data.
- Email notification system for significant changes in invoicing data.
- User-friendly graphical interface for data visualization.

How 'aws-resource-validator-invoicing' is Utilized:
- The package provides pre-defined Pydantic models that accurately represent AWS invoicing data structures. These models are used to validate the integrity and correctness of the imported invoicing data, ensuring that all necessary fields are present and formatted correctly. By leveraging these models, the application can perform robust validation checks and enforce data consistency, which is crucial for accurate invoicing analysis.

💬 Discussion Feed

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