aws-resource-validator-artifact

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity, but the incomplete maintainer's author information and the apparent newness or inactivity of the maintainer's account raise concerns about its provenance.

  • Incomplete maintainer's author information.
  • Account seems new or inactive.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of secrets and credentials.
  • Metadata: The maintainer's author information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 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 (303 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-artifact 
Create a Python-based command-line tool named 'AWS Artifact Validator' that leverages the 'aws-resource-validator-artifact' package to validate AWS resource artifacts against predefined schemas. This tool will help developers ensure their AWS resource definitions comply with best practices and standards, enhancing security and reliability.

### Project Scope:
1. **Artifact Validation**: Implement functionality to validate various types of AWS artifacts such as CloudFormation templates, IAM policies, and Lambda functions against pre-defined Pydantic models from the 'aws-resource-validator-artifact' package.
2. **User-Friendly Interface**: Develop a simple yet intuitive command-line interface allowing users to specify the path to their artifact file(s) and select the type of validation they wish to perform.
3. **Error Reporting**: Enhance usability by providing clear and actionable error messages when an artifact fails validation. These messages should include specific details about what part of the artifact does not conform to the schema.
4. **Custom Schema Support**: Allow users to define their own schemas using the Pydantic models provided by the package, enabling customization based on organizational requirements.
5. **Integration with CI/CD Pipelines**: Design the tool to integrate seamlessly into CI/CD workflows, ensuring that all changes to AWS resource definitions pass validation before deployment.

### Utilization of 'aws-resource-validator-artifact':
- Use the package's Pydantic models to define and validate the structure and content of AWS artifacts.
- Leverage the package's namespace extension capabilities to extend or modify existing models if necessary for custom validation rules.
- Integrate the validation logic directly within the tool's codebase, utilizing the package's classes and methods to perform validation checks.

### Expected Outcome:
By the end of this project, you will have developed a robust, user-friendly tool that significantly improves the quality and reliability of AWS resources through automated validation. This tool will serve as a valuable asset for teams looking to streamline their development processes while maintaining high standards of security and compliance.

💬 Discussion Feed

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