aws-resource-validator-workdocs

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risk indicators with no network calls, shell executions, obfuscations, or credential risks. The metadata risk is slightly elevated due to incomplete maintainer information.

  • No network calls
  • Incomplete maintainer information
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 maintainer's author information is incomplete and they may be new or inactive, which raises some concern but does not strongly indicate malicious intent.

📦 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-workdocs 
Develop a command-line utility named 'WorkDocsAuditTool' that leverages the 'aws-resource-validator-workdocs' package to validate and audit resources within Amazon WorkDocs. This tool will assist administrators and developers in ensuring their WorkDocs configurations meet specific compliance and security standards. Here’s a detailed breakdown of the application's requirements and functionalities:

1. **Resource Validation**: The utility should allow users to input a configuration file (JSON format) detailing various WorkDocs resources such as Users, Folders, Documents, etc. The 'aws-resource-validator-workdocs' package will be used to validate these configurations against predefined schemas provided by Pydantic v2 models.

2. **Audit Report Generation**: After validation, the tool should generate an audit report that highlights any discrepancies or potential security risks in the resource configurations. This report should include suggestions on how to rectify any issues found.

3. **Integration with AWS SDK for Python (Boto3)**: The application should integrate with Boto3 to fetch live data from a user's WorkDocs environment for comparison with the validated configurations. This ensures that the audit is based on actual current state data.

4. **User-Friendly Interface**: Provide a simple command-line interface where users can specify the configuration file path and choose whether to run a dry-run (validation only) or a full audit (validation + comparison with live data).

5. **Customizable Compliance Rules**: Allow users to define custom compliance rules for certain fields in the WorkDocs resources. For example, setting a minimum password length for user accounts or requiring two-factor authentication.

6. **Logging and Error Handling**: Implement logging for all operations performed by the tool, including validation results and any errors encountered during execution. Logs should be stored in a structured format for easy review and troubleshooting.

7. **Help and Documentation**: Include comprehensive help documentation and examples for how to use the tool effectively, including sample configuration files and common compliance rule settings.

By utilizing the 'aws-resource-validator-workdocs' package, you'll ensure that your application adheres to best practices in terms of data validation and model schema definition, making it robust and scalable for future updates.

💬 Discussion Feed

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