aws-resource-validator-docdb-elastic

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity such as network calls, shell execution, or credential harvesting. However, the maintainer's metadata raises some concerns due to an inactive or newly created account without a proper author name.

  • Low risk of network calls, shell execution, obfuscation, and credential harvesting.
  • Maintainer metadata is suspicious with a potentially inactive or new account lacking a proper author name.
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 the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, 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 (318 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-docdb-elastic 
Create a Python-based utility named 'DocDB-Elastic Health Checker' that leverages the 'aws-resource-validator-docdb-elastic' package to validate and monitor Amazon DocumentDB and Amazon ElastiCache resources. This utility should allow users to input their AWS resource details and then validate these against predefined Pydantic models provided by the package. The application will output whether each resource configuration is valid according to AWS best practices and standards.

Steps:
1. Set up a virtual environment and install the required packages, including 'aws-resource-validator-docdb-elastic'.
2. Create a function to load AWS resource configurations from a YAML file or user input.
3. Use Pydantic models from 'aws-resource-validator-docdb-elastic' to validate the configurations.
4. Implement a feature to display validation results, indicating which configurations pass or fail validation.
5. Extend functionality to include recommendations for fixing invalid configurations based on common issues identified by the package authors.
6. Add logging capabilities to record validation outcomes and any error messages.
7. Develop a command-line interface (CLI) for easy interaction with the utility.
8. Write unit tests to ensure the application functions correctly under various scenarios.

Features:
- Configuration loading from YAML files or direct user input.
- Real-time validation using Pydantic models from 'aws-resource-validator-docdb-elastic'.
- Detailed validation reports with pass/fail statuses.
- Recommendations for fixing invalid configurations.
- Logging of all validation processes and outcomes.
- User-friendly CLI for easy interaction.
- Comprehensive unit testing suite.

💬 Discussion Feed

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