aws-resource-validator-comprehend

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks across all categories except metadata, where the maintainer's account status is concerning. This combined with the lack of detailed author information warrants further scrutiny.

  • New or inactive maintainer account
  • Lack of detailed author 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 detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of sensitive information.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which raises some suspicion but does not strongly indicate 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 (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-comprehend 
Create a mini-application named 'ComprehendAnalyzer' that leverages the 'aws-resource-validator-comprehend' Python package to analyze and validate AWS Comprehend resources. This tool should enable users to input various AWS Comprehend resource configurations and receive validation feedback based on Pydantic v2 models provided by the package. The application should support the following functionalities:

1. **Resource Validation**: Users should be able to input JSON configurations for different AWS Comprehend resources such as 'DetectSentiment', 'StartDocumentTextDetection', etc., and the application will validate these configurations against the Pydantic models to ensure they meet the required schema.
2. **Error Reporting**: In case of invalid configurations, the application should provide detailed error messages indicating which fields are incorrect and why.
3. **Configuration Suggestions**: For each detected error, the application should suggest possible corrections or valid configurations.
4. **Interactive Mode**: Implement an interactive mode where users can iteratively correct their configurations until they become valid.
5. **Batch Processing**: Allow users to upload a file containing multiple resource configurations and get batch validation results.
6. **Documentation and Help**: Provide comprehensive documentation and a help section explaining common errors and best practices for configuring AWS Comprehend resources.

The 'aws-resource-validator-comprehend' package is utilized to define and validate the structure of AWS Comprehend resource configurations using Pydantic v2 models. These models serve as the basis for validating user inputs and generating meaningful error messages and suggestions. Your task is to design and implement this mini-application ensuring it provides a user-friendly interface and accurate validation feedback.

💬 Discussion Feed

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