aws-resource-validator-fis

v2.0.3 safe
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with minimal risks observed. While the metadata risk is slightly elevated due to incomplete maintainer information, there are no indications of malicious activities such as network calls, shell executions, or obfuscations.

  • Low risk scores across all categories
  • Incomplete maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no direct system command invocation.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
  • Metadata: The maintainer's author information is incomplete, and they may be new or inactive, raising some concern but not enough to conclusively indicate malicious intent.

📦 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-fis 
Your task is to develop a Python-based utility called 'FIS Resource Validator' that leverages the 'aws-resource-validator-fis' package to validate AWS Fault Injection Simulator (FIS) resources according to specific criteria. This utility will help users ensure their FIS experiment configurations are valid before they are deployed. Here’s a detailed breakdown of the requirements and steps for building this utility:

1. **Project Setup**: Begin by setting up your Python environment and installing the required packages, including 'aws-resource-validator-fis'. Ensure you have the necessary AWS credentials configured.

2. **Input Handling**: Design the utility to accept either a JSON file or a direct JSON input from the user containing the FIS experiment configuration. This JSON should include all necessary details such as target resource ARNs, fault types, and injection parameters.

3. **Validation Logic**: Utilize the 'aws-resource-validator-fis' package to create validation schemas for different aspects of the FIS experiment configurations. These schemas should cover various scenarios, such as validating target resource existence, checking for correct parameter values, and ensuring compliance with AWS policies.

4. **Error Reporting**: Implement a feature that provides detailed error reporting when a configuration fails validation. This should include not only the failure reason but also suggestions on how to fix the issues.

5. **Output Generation**: Upon successful validation, generate a summary report detailing the validated configuration along with any warnings or recommendations for improvement. For failed validations, provide a comprehensive error log.

6. **User Interface**: While primarily command-line driven, consider adding basic CLI options for specifying input/output files and verbosity levels. Additionally, explore integrating a simple GUI using Tkinter for easier user interaction.

7. **Testing**: Develop a suite of test cases to validate the functionality of your utility under different scenarios, ensuring it handles both valid and invalid inputs gracefully.

8. **Documentation**: Write clear documentation explaining how to install, configure, and use your utility, including examples of valid and invalid FIS experiment configurations.

By following these steps, you'll create a robust tool that significantly simplifies the process of validating AWS FIS experiment configurations, thereby reducing deployment risks and improving overall system reliability.

💬 Discussion Feed

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