aws-resource-validator-securitylake

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk in terms of network, shell, and obfuscation activities. However, the incomplete author information and the maintainer's single package history raise concerns about potential supply-chain risks.

  • Incomplete author information
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author information is incomplete and the maintainer has only one package, which may 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 (315 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-securitylake 
Develop a Python-based command-line tool named 'SecurityLakeInspector' that leverages the 'aws-resource-validator-securitylake' package to validate and analyze AWS Security Lake resources. This tool should enable users to check the compliance and security posture of their Security Lake configurations against predefined standards and best practices. Here are the key steps and features your project should include:

1. **Setup**: Install the necessary dependencies including 'aws-resource-validator-securitylake', boto3 for AWS interactions, and typer for command-line interface (CLI) functionality.
2. **Resource Validation**: Implement functions that use the 'aws-resource-validator-securitylake' models to fetch and validate Security Lake resources from a user's AWS account. These validations should cover aspects such as data lake configuration, S3 bucket policies, and IAM roles.
3. **Compliance Checks**: Integrate compliance checks based on AWS best practices and industry standards (e.g., CIS benchmarks). These checks should assess the current state of the Security Lake resources and provide recommendations for improvement.
4. **Report Generation**: Develop a feature that generates comprehensive reports detailing the validation results and compliance status. Reports should be easily readable and include actionable insights.
5. **Interactive CLI**: Create an interactive command-line interface where users can input specific resource IDs or ARNs, choose which compliance checks to run, and view real-time feedback.
6. **Customization Options**: Allow users to customize the validation rules and compliance checks according to their organization's specific needs.
7. **Error Handling & Logging**: Ensure robust error handling and logging mechanisms are in place to capture and report any issues encountered during the validation process.

The 'aws-resource-validator-securitylake' package will be central to defining the structure and validation criteria for AWS Security Lake resources, ensuring that all checks and analyses align with AWS's own guidelines and best practices.

💬 Discussion Feed

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