aws-resource-validator-wellarchitected

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows very low risks in terms of network, shell, and obfuscation activities, with no detected credential harvesting. However, the incomplete author information slightly increases the metadata risk, making it necessary to monitor the package's updates.

  • Incomplete author information
  • No detected malicious activities
Per-check LLM notes
  • Network: No network calls detected, which is normal for packages not requiring external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
  • Metadata: The author information is incomplete, which raises some suspicion but does not necessarily indicate malice.

📦 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 (324 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-wellarchitected 
Your task is to develop a Python-based CLI tool named 'WellArchitectedAdvisor'. This tool will help AWS users validate their resource configurations against the best practices defined in the AWS Well-Architected Framework. The application should be designed to analyze AWS resources (like EC2 instances, S3 buckets, RDS databases, etc.) and provide feedback on how well they align with the best practices outlined in the framework. The tool should also suggest improvements where necessary.

Core Features:
1. **Resource Validation**: Integrate the 'aws-resource-validator-wellarchitected' package to define validation rules based on the AWS Well-Architected Framework. Use these rules to assess various AWS resources.
2. **Configuration Analysis**: Allow users to input their AWS configuration details (via a YAML file or command-line arguments). The tool should then parse these inputs and compare them against the predefined validation rules.
3. **Feedback and Recommendations**: Provide detailed feedback on each resource, highlighting any discrepancies from the best practices. For each discrepancy, offer actionable recommendations on how to improve the configuration.
4. **Report Generation**: Generate a comprehensive report summarizing the findings. This report should include overall compliance scores, specific issues identified, and improvement suggestions.
5. **Customization Options**: Enable users to customize certain aspects of the validation process, such as selecting which categories of the Well-Architected Framework to focus on (e.g., Security, Performance Efficiency).

Steps to Build the Application:
1. **Setup Project Structure**: Initialize a new Python project and install the required dependencies, including 'aws-resource-validator-wellarchitected'.
2. **Define Validation Models**: Utilize the Pydantic v2 models provided by 'aws-resource-validator-wellarchitected' to define your validation logic. Customize these models if needed to fit your specific use case.
3. **Implement Resource Parsing**: Develop functionality to read and parse user-provided AWS resource configurations. Ensure that this functionality supports multiple input formats (YAML files, JSON, command-line arguments).
4. **Validation Logic**: Implement the core validation logic using the models defined in step 2. This logic should compare the parsed resources against the validation rules and generate appropriate feedback.
5. **Generate Reports**: Create a reporting module that can produce human-readable reports summarizing the validation results. These reports should be easy to understand and actionable.
6. **User Interface**: Design a simple yet effective CLI interface for interacting with the tool. Consider adding options for customization and specifying input/output formats.
7. **Testing and Documentation**: Write tests to ensure the reliability of your application. Also, create thorough documentation detailing how to install, configure, and use the tool effectively.

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