aws-resource-validator-macie2

v2.0.3 safe
3.0
Low Risk

Pydantic v2 models for AWS macie2, shipped as a PEP 420 namespace extension of aws-resource-validator.

🤖 AI Analysis

Final verdict: SAFE

The package has no detected network calls, shell executions, obfuscations, or credential harvesting attempts, which significantly lowers the risk of malicious intent. However, the metadata risk score is elevated due to sparse author details.

  • No network calls detected
  • Sparse author details
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity for a tool focused on local resource validation.
  • Shell: No shell execution patterns detected, aligning with the expected behavior of a package that does not require system-level changes.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's details are sparse, indicating potential lack of transparency or newness to PyPI.

📦 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 (297 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-macie2 
Your task is to develop a Python-based utility named 'Macie2AuditTool' that leverages the 'aws-resource-validator-macie2' package to audit and validate AWS Macie2 resources. This tool will help administrators ensure that their Macie2 configurations comply with organizational security policies and best practices. Here’s a detailed plan for your project:

1. **Project Setup**: Start by setting up a virtual environment for your project and installing the necessary dependencies, including 'aws-resource-validator-macie2'. Ensure you also include boto3, the AWS SDK for Python, for interacting with AWS services.

2. **Resource Validation**: Utilize the Pydantic models provided by 'aws-resource-validator-macie2' to define and validate the structure of Macie2 resources such as findings, custom data identifiers, and member accounts. Your tool should be able to load these resources from an input file (JSON format) and validate them against the defined schemas.

3. **Security Compliance Check**: Implement a feature where the tool checks each validated resource against a set of predefined security compliance rules. For example, it could verify if sensitive data identifiers are correctly configured or if certain actions are restricted based on organizational policies.

4. **Reporting**: Develop a reporting module that generates a comprehensive report summarizing the validation results and compliance checks. The report should highlight any non-compliant resources and provide recommendations for remediation.

5. **CLI Interface**: Create a command-line interface (CLI) for the tool using Python’s argparse library. Users should be able to specify the input file containing the Macie2 resources, select which compliance checks to run, and choose the output format for the report.

6. **Optional Features**:
   - Integration with AWS Lambda to schedule periodic audits automatically.
   - Support for multiple input files or directories.
   - Email notification of audit results.

7. **Testing**: Write unit tests to ensure the correctness of your validation logic and compliance checks. Use pytest for testing.

8. **Documentation**: Provide clear documentation on how to install, configure, and use the tool. Include examples of valid and invalid input files, and demonstrate how to interpret the reports.

This project aims to simplify the process of ensuring AWS Macie2 configurations adhere to security standards, making it easier for organizations to maintain compliance across their cloud environments.

💬 Discussion Feed

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