aws-resource-validator-opensearch

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks in terms of network, shell execution, obfuscation, and credential handling. However, the metadata risk score is elevated due to sparse and possibly inactive author details, which raises some suspicion.

  • Metadata risk score is 3 out of 10
  • Sparse and possibly inactive author details
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating a low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting legitimate usage without the risk of stealing secrets.
  • Metadata: The author's details are sparse and the account seems new or inactive, raising some suspicion but not definitive 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 (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-opensearch 
Create a command-line utility named 'OpensearchValidator' using Python that leverages the 'aws-resource-validator-opensearch' package to validate configurations for Amazon OpenSearch Service domains. This tool will assist DevOps engineers and cloud administrators in ensuring their OpenSearch domain configurations adhere to best practices and meet compliance requirements.

The application should include the following features:
1. **Configuration Loading**: Allow users to load configuration files from local storage or directly input configurations via the command line.
2. **Validation Logic**: Implement validation logic based on the Pydantic v2 models provided by the 'aws-resource-validator-opensearch' package to check if the configurations are valid according to AWS specifications.
3. **Detailed Reports**: Generate comprehensive reports that highlight any issues found during the validation process, including suggestions for corrections.
4. **Interactive Mode**: Provide an interactive mode where users can modify and revalidate configurations until they pass all checks.
5. **Integration Testing**: Include integration tests that use sample configurations to ensure the validation process works as expected.

To utilize the 'aws-resource-validator-opensearch' package, you'll need to import its models and use them to define schemas against which your configurations will be validated. Ensure that your code demonstrates best practices in Python and follows PEP8 style guidelines.

💬 Discussion Feed

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