aws-resource-validator-appconfig

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activities such as network calls, shell executions, or credential harvesting. The only elevated concern is the incomplete maintainer's profile, which does not necessarily indicate malicious intent.

  • Low network risk
  • No shell risk detected
  • No credential risk detected
  • Incomplete maintainer profile
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 suspicious command-line activity.
  • 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 maintainer has an incomplete profile and may be new or inactive, but no other suspicious flags were raised.

📦 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 (306 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-appconfig 
Create a Python-based CLI tool named 'AppConfigValidator' that leverages the 'aws-resource-validator-appconfig' package to validate AWS AppConfig resources. This tool should allow users to specify one or more AppConfig resources (such as environments, deployments, and configurations) via command-line arguments and validate them against predefined schemas provided by the 'aws-resource-validator-appconfig' package. The validation process should check if the specified resources adhere to AWS best practices and standards, providing detailed feedback on any issues found.

### Features:
- **Resource Validation**: Validate AppConfig resources like environments, deployments, and configurations against Pydantic models from the 'aws-resource-validator-appconfig' package.
- **Detailed Feedback**: For each resource, provide a detailed report indicating whether it passes validation, along with specific reasons for any failures.
- **Command-Line Interface**: Implement a user-friendly CLI that accepts input parameters for specifying the type of resource to validate and the resource details.
- **Configuration File Support**: Allow users to specify resources through a configuration file (e.g., YAML or JSON), which the tool will read and validate accordingly.
- **Integration with AWS SDK**: Use the Boto3 library to interact with AWS services, fetching the actual AppConfig resources to compare against the validation models.
- **Customizable Validation Rules**: Provide options for users to customize validation rules based on their specific requirements or organizational policies.
- **Output Formats**: Support different output formats for the validation results, such as plain text, JSON, or HTML.

### Steps to Build the Application:
1. **Setup Project Structure**: Create a Python project structure that includes subdirectories for source code, tests, and configuration files.
2. **Install Dependencies**: Install necessary packages including 'aws-resource-validator-appconfig', 'boto3', and 'click' for building the CLI.
3. **Define CLI Commands**: Use Click to define commands for validating different types of AppConfig resources.
4. **Implement Resource Validators**: Write functions that use the 'aws-resource-validator-appconfig' package to validate the resources according to the Pydantic models.
5. **Fetch Resources from AWS**: Implement logic to fetch the actual AppConfig resources using Boto3.
6. **Compare and Report**: Compare fetched resources with the validation models and generate detailed reports on compliance.
7. **Support Configuration Files**: Add functionality to read resource specifications from configuration files.
8. **Customization Options**: Allow users to extend validation rules by adding custom schemas or modifying existing ones.
9. **Output Formatting**: Develop support for multiple output formats to meet different user needs.
10. **Testing and Documentation**: Write unit tests and create comprehensive documentation for the CLI tool.

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