aws-resource-validator-identitystore

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, with no indications of network calls, shell execution, obfuscation, or credential harvesting. The metadata risk is slightly elevated due to incomplete maintainer information.

  • No network calls detected.
  • Incomplete maintainer 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 patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, suggesting legitimate use.
  • Credentials: No credential harvesting patterns detected, indicating no risk of credential theft.
  • Metadata: The maintainer's author information is incomplete and may indicate a less experienced or new developer.

📦 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 (318 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-identitystore 
Create a Python-based mini-application named 'IdentityStoreInspector' that leverages the 'aws-resource-validator-identitystore' package to validate and inspect AWS Identity Store resources. This application should serve as a tool for developers and system administrators to ensure compliance and correctness of their AWS Identity Store configurations. The app will connect to AWS Identity Store, fetch user and group data, and validate these against predefined schemas provided by the 'aws-resource-validator-identitystore' package. Here are the steps and features your application should include:

1. **Setup**: Initialize your Python environment with necessary AWS SDK and 'aws-resource-validator-identitystore' packages. Ensure you have the required IAM permissions to access AWS Identity Store.
2. **Authentication**: Implement a secure way to authenticate with AWS Identity Store using either temporary credentials or long-term access keys. Use Boto3 for AWS service interactions.
3. **Resource Fetching**: Develop functions to fetch users and groups from AWS Identity Store. These functions should handle pagination and errors gracefully.
4. **Validation**: Utilize the pydantic models from 'aws-resource-validator-identitystore' to validate fetched resources against the defined schemas. This includes checking for completeness, correctness, and adherence to best practices.
5. **Reporting**: Create a reporting mechanism that outputs validation results in a human-readable format. Include options for exporting reports to CSV or JSON files.
6. **Customization**: Allow users to customize validation rules by extending or modifying the provided schemas. This could involve adding custom fields or adjusting existing ones based on specific organizational requirements.
7. **User Interface**: While command-line interface (CLI) is acceptable, consider developing a simple web interface using Flask or Django for more interactive usage. This UI should allow users to input AWS credentials, select resources to inspect, and view validation results.
8. **Testing**: Write comprehensive unit tests for all components of the application, focusing on edge cases and error handling scenarios.
9. **Documentation**: Provide clear documentation on how to install, configure, and use 'IdentityStoreInspector'. Include examples and best practices for integration into CI/CD pipelines.

By following these steps, 'IdentityStoreInspector' will become a valuable tool for maintaining high standards of security and compliance within AWS Identity Store environments.

💬 Discussion Feed

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