aws-resource-validator-mpa

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risk indicators with no network, shell, obfuscation, or credential risks detected. The metadata risk is slightly elevated due to the maintainer's account status.

  • No network calls detected
  • Maintainer account is new or inactive
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external AWS API interactions.
  • Shell: No shell execution patterns detected, aligning with expectations for a non-executable Python package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The maintainer has a new or inactive account and lacks detailed author information, raising some suspicion but not conclusive evidence of 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 (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-mpa 
Develop a Python-based mini-application named 'AWS Resource Compliance Checker' that leverages the 'aws-resource-validator-mpa' package to validate AWS resources against specific compliance standards. This tool will assist DevOps teams in ensuring their cloud infrastructure adheres to company-defined best practices and regulatory requirements. Here’s a detailed breakdown of the project scope and implementation steps:

1. **Project Overview**: Create a command-line interface (CLI) application that takes input from a YAML configuration file specifying AWS resource types and compliance rules. The application will use the 'aws-resource-validator-mpa' package to validate these resources against the specified rules.

2. **Core Features**:
   - **Resource Validation**: Implement functionality to validate various AWS resources (e.g., EC2 instances, S3 buckets) using Pydantic models provided by 'aws-resource-validator-mpa'.
   - **Compliance Rules Configuration**: Allow users to define custom compliance rules within the YAML configuration file. These rules could include parameters like encryption settings, public access permissions, etc.
   - **Report Generation**: After validation, generate a report summarizing the compliance status of each resource, highlighting any non-compliant items.
   - **Integration with AWS SDK**: Use the Boto3 library to interact with AWS services and retrieve necessary information about the resources being validated.

3. **Implementation Steps**:
   - **Setup Project Environment**: Initialize a Python project environment and install necessary packages including 'aws-resource-validator-mpa', 'pydantic', 'boto3', and 'pyyaml'.
   - **Define Models**: Utilize the 'aws-resource-validator-mpa' package to define Pydantic models for different AWS resources. Ensure these models encapsulate all relevant attributes needed for compliance checks.
   - **Create CLI Interface**: Develop a CLI using argparse or similar to accept user inputs, such as the path to the YAML configuration file.
   - **Parse Configuration File**: Implement code to parse the YAML configuration file containing the compliance rules.
   - **Validate Resources**: Write logic to fetch data from AWS using Boto3, compare it against the defined models and compliance rules, and flag any discrepancies.
   - **Generate Reports**: Format and output validation results into a human-readable report, possibly saving it as a text or PDF file.
   - **Testing and Documentation**: Thoroughly test the application under various scenarios and document its usage clearly, including examples of valid YAML configurations and expected outputs.

This project aims to streamline the process of maintaining AWS resource compliance, providing DevOps professionals with a powerful yet easy-to-use tool.

💬 Discussion Feed

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