aws-resource-validator-grafana

v2.0.3 safe
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories with no detected network calls, shell executions, or obfuscation techniques. The metadata risk is slightly elevated due to the maintainer's incomplete profile and new account.

  • No network calls detected
  • No shell execution detected
  • Maintainer has incomplete profile and new account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has an incomplete profile and a new account, which raises some concerns but does not strongly indicate malicious intent.

📦 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 (300 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-grafana 
Create a Python-based utility named 'GrafanaResourceChecker' that leverages the 'aws-resource-validator-grafana' package to validate AWS Grafana resources against predefined schemas. This tool will serve as a valuable asset for DevOps engineers and cloud administrators who need to ensure their Grafana configurations adhere to best practices and standards. Here’s a detailed breakdown of the project requirements and steps:

1. **Project Setup**: Begin by setting up a new Python environment and installing necessary packages including 'aws-resource-validator-grafana'. Ensure your project structure is clean and organized.

2. **Configuration File**: Design a configuration file where users can specify the path to their Grafana resource files (JSON format). These files typically contain details about dashboards, datasources, alert channels, etc.

3. **Validation Logic**: Utilize the 'aws-resource-validator-grafana' package to define validation rules based on Pydantic v2 models. Implement functions that load these resource files and validate them against the defined schemas. Provide meaningful error messages if any discrepancies are found.

4. **Interactive Mode**: Add an interactive mode where users can input paths directly through command line arguments or stdin. This feature should also allow for specifying which type of resource (dashboard, datasource, etc.) is being validated.

5. **Reporting**: Integrate a reporting mechanism that generates a summary report upon completion of validation. This report should include a list of all resources checked, validation status, and any errors encountered.

6. **Testing**: Develop comprehensive unit tests to cover all aspects of the validation logic and reporting functionalities. Use mock data for testing purposes to simulate various scenarios.

7. **Documentation**: Write clear and concise documentation that guides users through installation, configuration, usage, and troubleshooting common issues.

8. **Deployment**: Prepare a deployment package that includes all necessary dependencies and setup scripts for easy deployment on different environments.

This project aims to streamline the process of validating AWS Grafana resources, ensuring they meet organizational standards and improving overall security and reliability.

💬 Discussion Feed

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