aws-resource-validator-marketplace-catalog

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network, shell, obfuscation, and credential handling. However, the incomplete author information and potentially inactive account raise concerns about its legitimacy.

  • Incomplete author information
  • Potentially inactive account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting legitimate use without hidden malicious intent.
  • Metadata: The author information is incomplete and the account seems new or inactive, 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 (336 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-marketplace-catalog 
Create a Python-based CLI tool named 'MarketplaceAuditTool' which leverages the 'aws-resource-validator-marketplace-catalog' package to validate and audit AWS Marketplace Catalog resources. This tool will serve as a comprehensive solution for developers and administrators who need to ensure their AWS Marketplace resources meet specific criteria before deployment or modification.

Step 1: Setup the Project
- Initialize a new Python project and install necessary dependencies including 'aws-resource-validator-marketplace-catalog'.

Step 2: Define Core Functionality
- Implement functions to connect to AWS Marketplace Catalog using Boto3 SDK.
- Utilize 'aws-resource-validator-marketplace-catalog' to define validation rules for various resource types (e.g., products, status updates).
- Create a function to fetch resources from AWS Marketplace Catalog and validate them against predefined rules.

Step 3: Enhance with Additional Features
- Add a feature to automatically correct minor issues found during validation, such as updating descriptions or statuses.
- Implement logging to track validation results and actions taken.
- Allow users to customize validation rules through configuration files or command-line arguments.

Step 4: Build the CLI Interface
- Design a user-friendly CLI interface allowing users to select validation targets (all resources, specific types, individual IDs).
- Include options for running validations in dry-run mode to preview changes without applying them.
- Support batch processing of multiple resources.

Step 5: Testing and Documentation
- Write unit tests for each core functionality to ensure reliability.
- Provide detailed documentation on installation, usage, and customization options.
- Publish the project on GitHub with clear README instructions.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!