aws-resource-validator-cloudfront

v2.0.3 suspicious
4.0
Medium Risk

Pydantic v2 models for AWS cloudfront, 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, shell execution, and obfuscation. However, the metadata risk score is elevated due to the maintainer's account status and lack of detailed author information, raising concerns about potential supply-chain attacks.

  • Metadata risk due to new/inactive maintainer account
  • Lack of detailed author information
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution detected, which is expected as typical Python packages do not execute system commands unless explicitly designed to.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks detailed author information, which may indicate a less experienced or potentially suspicious actor.

📦 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 (309 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-cloudfront 
Create a command-line utility named 'CloudFrontValidator' using Python that leverages the 'aws-resource-validator-cloudfront' package to validate and manage CloudFront distributions efficiently. This tool should serve as a robust solution for developers and DevOps engineers to ensure their CloudFront configurations adhere to best practices and AWS standards.

### Features:
- **Configuration Validation**: Allow users to input their CloudFront distribution configurations via a YAML file. The utility should use the 'aws-resource-validator-cloudfront' package to validate these configurations against Pydantic models, ensuring they meet AWS requirements.
- **Error Reporting**: If any errors or warnings are found during validation, provide a detailed report highlighting issues such as missing required fields, incorrect values, or deprecated settings.
- **Interactive Mode**: Implement an interactive mode where users can input individual parameters and receive real-time feedback on their validity according to the CloudFront schema.
- **CloudFormation Integration**: Extend functionality to support CloudFormation templates, validating nested CloudFront resources within larger infrastructure definitions.
- **Custom Rule Support**: Enable users to define custom validation rules based on specific organizational policies or security guidelines.
- **Documentation & Help**: Include comprehensive documentation and a help section that guides users through setup, configuration, and usage of the tool.

### Utilization of 'aws-resource-validator-cloudfront':
This package provides essential Pydantic models for AWS CloudFront, which your utility will use to parse and validate user inputs. By integrating these models, you ensure that all configurations are correctly structured and comply with AWS CloudFront specifications. Additionally, leverage the package's namespace extension capabilities to enhance the utility's flexibility and compatibility with evolving AWS services.

💬 Discussion Feed

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