aws-resource-validator-workspaces

v2.0.3 suspicious
4.0
Medium Risk

Pydantic v2 models for AWS workspaces, 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 maintainer's metadata raises some concerns due to a lack of a proper author name and limited package history.

  • Maintainer has a new or inactive account
  • Lack of proper author name
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 the package does not execute system commands.
  • 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 with limited package history and lacks a proper author name, which may indicate potential risk.

📦 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-workspaces 
Create a utility named 'WorkspaceAuditor' that leverages the 'aws-resource-validator-workspaces' package to audit and validate AWS WorkSpaces resources. This tool should provide developers and system administrators with an easy-to-use interface to check the integrity and compliance of their WorkSpaces setup against predefined standards. Here’s a step-by-step guide on how to build this utility:

1. **Setup Project**: Initialize a new Python project and install the required packages, including 'aws-resource-validator-workspaces', 'boto3' for AWS SDK access, and 'typer' for command-line argument parsing.
2. **Define Validation Rules**: Use the Pydantic models provided by 'aws-resource-validator-workspaces' to define validation rules. These rules will include checks such as ensuring all WorkSpaces have the correct volume type, that user access policies comply with organizational guidelines, and that all instances are running the latest software updates.
3. **Integrate AWS SDK**: Utilize 'boto3' to interact with AWS services. Your utility should be able to fetch information about WorkSpaces from AWS and pass it through your validation rules.
4. **Command Line Interface**: Implement a simple CLI using 'typer'. Users should be able to specify which WorkSpaces to audit, choose specific validation rules to apply, and get a report of any violations or issues found.
5. **Report Generation**: After running audits, generate a detailed report. This report should highlight any non-compliant items and suggest corrective actions. It could also include metrics like the percentage of compliant WorkSpaces.
6. **Testing and Documentation**: Write unit tests to ensure your validation logic works correctly and document your tool thoroughly, explaining how to install, configure, and use it effectively.
7. **Optional Features**: Consider adding optional features such as scheduling audits automatically, sending email notifications upon completion, and integrating with other AWS services like SNS for alerting.

This project aims to streamline the process of maintaining secure and efficient WorkSpaces environments, making it easier for teams to adhere to best practices without manual intervention.

💬 Discussion Feed

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