aws-resource-validator-gamelift

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risk indicators based on the analysis notes provided, with no signs of malicious activities such as network calls or credential harvesting. However, the metadata risk due to the author's profile raises slight concern.

  • Low risk scores across all categories
  • Metadata risk due to author's profile
Per-check LLM notes
  • Network: No network calls suggest normal operation if the package is purely local.
  • Shell: No shell execution detected indicates no immediate risk from command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has a potentially suspicious profile with a missing name and limited package history, but no other red 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 (303 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-gamelift 
Create a Python-based utility called 'GameliftHealthChecker' that leverages the 'aws-resource-validator-gamelift' package to monitor and validate AWS GameLift resources. This tool should provide real-time insights into the health and status of GameLift fleets, ensuring they meet specific criteria defined by the user. The application will fetch data from AWS GameLift and validate it against Pydantic models provided by 'aws-resource-validator-gamelift'. Here’s a detailed breakdown of the project requirements:

1. **Setup**: Begin by setting up a virtual environment and installing necessary packages including 'boto3', 'aws-resource-validator-gamelift', and 'pydantic'. Ensure your AWS credentials are properly configured.

2. **Data Fetching**: Implement functionality to retrieve information about GameLift fleets and other relevant resources from AWS. Use the 'boto3' library for interaction with AWS services.

3. **Validation Logic**: Utilize the Pydantic models from 'aws-resource-validator-gamelift' to validate fetched data. Define rules and thresholds for fleet health such as player latency, instance hours used, and fleet status.

4. **Alert System**: Develop an alert system that notifies users via email or SMS if any fleet fails validation checks. Users should be able to customize alert thresholds.

5. **User Interface**: Create a simple CLI interface using Python's 'argparse' module where users can specify which fleets to check, desired validation criteria, and alert preferences.

6. **Logging & Reporting**: Integrate logging to record all operations and results. Provide a feature to generate reports summarizing fleet health over time.

7. **Testing**: Write unit tests to ensure all components work correctly. Include tests for fetching data, validating against models, triggering alerts, and generating logs/reports.

8. **Documentation**: Prepare comprehensive documentation explaining how to install, configure, and use the GameliftHealthChecker utility. Include examples and best practices.

By completing this project, you'll have a robust tool for monitoring AWS GameLift resources, ensuring they meet operational standards and notifying stakeholders when issues arise.

💬 Discussion Feed

Leave a comment

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