aws-resource-validator-lex-models

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious behavior based on the analysis notes provided. The lack of network calls, shell executions, obfuscation, and credential harvesting all point towards a benign package.

  • No network calls detected
  • Incomplete author information
Per-check LLM notes
  • Network: No network call patterns detected, which may be unusual depending on the package's functionality. However, without additional context, it does not necessarily indicate malicious activity.
  • Shell: No shell execution patterns detected, which is normal and expected for a typical Python package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author information is incomplete, suggesting a potentially less experienced or inactive maintainer.

📦 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 (309 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-lex-models 
Develop a command-line tool that validates and manages Amazon Lex resources using the 'aws-resource-validator-lex-models' package. This tool will allow users to interactively validate their Amazon Lex model configurations against AWS standards, ensuring they meet all necessary requirements before deployment. The application should have the following functionalities:

1. **Resource Validation**: Users can input or upload their Amazon Lex model configurations (in JSON format), and the tool will validate these configurations against predefined Pydantic models provided by 'aws-resource-validator-lex-models'. The validation process should check for common errors such as missing fields, incorrect data types, and compliance with AWS best practices.

2. **Interactive Error Reporting**: If any issues are found during validation, the tool should provide detailed error messages indicating which parts of the configuration are problematic. It should also suggest possible fixes or improvements based on the specific errors encountered.

3. **Configuration Export**: After successful validation, the tool should allow users to export their validated configurations either back into a JSON file or directly to their AWS account through an integrated AWS SDK (such as Boto3).

4. **Customization Options**: Allow users to customize certain aspects of the validation process, such as specifying additional constraints or rules that go beyond the standard AWS requirements.

5. **Documentation Generation**: For each validated model, generate a human-readable documentation file that describes the structure of the model, including all attributes and their expected values, which can be useful for both developers and non-technical stakeholders.

To utilize the 'aws-resource-validator-lex-models' package effectively, you will need to import its Pydantic models and use them to define your validation schemas. Additionally, leverage the package's namespace extension capabilities to extend or modify existing models if needed. Ensure that your tool integrates seamlessly with AWS services and provides a user-friendly interface for managing Amazon Lex resources.

💬 Discussion Feed

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