aws-resource-validator-application-autoscaling

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks across network, shell, and obfuscation categories. However, the metadata risk score is moderately high due to sparse author details and possibly inactive author account, warranting further investigation.

  • Metadata risk score of 3/10
  • Sparse author details and possibly inactive author account
Per-check LLM notes
  • Network: No network calls detected, which is normal for packages that don't require external communications.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The author details are sparse and the account seems new or inactive, raising some suspicion but not conclusive evidence of malintent.

📦 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 (348 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-application-autoscaling 
Create a Python-based CLI tool named 'AutoScalerChecker' that leverages the 'aws-resource-validator-application-autoscaling' package to validate and manage AWS Application Auto Scaling resources. This tool will help developers and DevOps engineers ensure their auto-scaling policies, scalable targets, and scheduled actions are correctly configured and adhere to best practices.

### Key Features:
1. **Resource Validation**: Implement a feature to validate AWS Application Auto Scaling resources such as Scalable Targets, Policies, and Scheduled Actions against Pydantic models provided by the 'aws-resource-validator-application-autoscaling' package.
2. **Policy Creation/Modification**: Allow users to create and modify auto-scaling policies directly through the CLI, ensuring they comply with the defined validation rules.
3. **Scheduled Actions Management**: Provide functionality to manage scheduled actions including creation, deletion, and modification, all while adhering to the validation criteria set by the package.
4. **Integration with AWS CLI**: Enable seamless integration with existing AWS CLI configurations for authentication and resource access.
5. **Detailed Reporting**: Offer comprehensive reports on validation results, highlighting any discrepancies or potential issues in the configuration of auto-scaling resources.
6. **Custom Rule Support**: Allow users to define custom validation rules beyond those provided by default, enhancing flexibility and adaptability to specific organizational requirements.
7. **Interactive Mode**: Include an interactive mode where users can explore and modify their auto-scaling configurations step-by-step with real-time validation feedback.

### Utilization of 'aws-resource-validator-application-autoscaling':
- Use the Pydantic models from the package to define the structure and constraints for auto-scaling resources during validation.
- Leverage these models to automatically generate validation errors when configurations deviate from expected standards.
- Implement the package’s namespace extension capabilities to enhance the tool's ability to understand and work with complex auto-scaling scenarios.
- Ensure all operations performed by the tool are validated against these models to maintain high standards of configuration correctness and consistency.

💬 Discussion Feed

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