aws-resource-validator-ram

v2.0.3 suspicious
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risk factors but the metadata risk score is elevated due to sparse and potentially inactive author information, raising suspicion about its legitimacy.

  • Sparse author information
  • Potentially inactive author account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or system exploitation.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is sparse and the account seems new or inactive, which could indicate potential risks.

📦 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 (288 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-ram 
Create a Python-based CLI tool named 'ResourceGuard' which leverages the 'aws-resource-validator-ram' package to validate and manage AWS RAM resources efficiently. This tool will serve as a robust solution for developers and system administrators looking to ensure their AWS RAM configurations adhere to best practices and compliance standards.

#### Project Scope:
1. **Resource Validation**: Implement functionality to validate AWS RAM resources using the Pydantic v2 models provided by the 'aws-resource-validator-ram' package. Users should be able to input resource details, and the tool will return validation results indicating whether the resource configuration is compliant or not.
2. **Configuration Management**: Allow users to manage AWS RAM resource configurations directly through the CLI. Features should include creating, updating, and deleting resources based on user inputs.
3. **Compliance Reporting**: Generate compliance reports summarizing the validation status of all managed resources. Reports should be exportable in formats such as CSV or JSON.
4. **Integration with AWS SDK**: Utilize the Boto3 library to interact with AWS services, ensuring seamless integration with existing AWS infrastructures.
5. **User Interface**: Develop a user-friendly CLI interface with clear prompts and error messages. The CLI should support both interactive and batch modes.

#### Core Features:
- **Validation Logic**: Use the 'aws-resource-validator-ram' package to define validation rules and perform real-time validation checks against AWS RAM resources.
- **Resource CRUD Operations**: Enable users to create (CR), read (R), update (U), and delete (D) AWS RAM resources via command-line interactions.
- **Customizable Compliance Rules**: Allow users to customize validation rules according to their specific compliance requirements.
- **Automated Reporting**: Automatically generate and save compliance reports after each validation run.
- **Security Measures**: Ensure all interactions with AWS services are secured using IAM roles and credentials management best practices.

#### Utilization of 'aws-resource-validator-ram':
- **Model Definitions**: Import and utilize the Pydantic v2 models from 'aws-resource-validator-ram' to define the structure of AWS RAM resources and their associated validation rules.
- **Data Validation**: Integrate these models into your validation logic to ensure data integrity and adherence to AWS standards before performing any operations on AWS resources.
- **Error Handling**: Leverage the validation capabilities of the package to provide meaningful feedback to users when resource configurations are invalid or non-compliant.

This project aims to streamline the process of managing and validating AWS RAM resources, making it easier for teams to maintain high standards of security and compliance across their cloud infrastructure.

💬 Discussion Feed

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