aws-resource-validator-servicediscovery

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no direct signs of malicious activity such as network calls, shell executions, or obfuscation. However, the incomplete author information and potentially new or inactive account raise concerns about its legitimacy.

  • Incomplete author information and possibly new/inactive account.
  • No detected malicious activities.
Per-check LLM notes
  • Network: No network calls detected, which is normal for packages that don't require external API interactions.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is incomplete and the account seems new or inactive, which raises some concern but does not 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 (327 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-servicediscovery 
Create a Python-based command-line tool that validates AWS Service Discovery resources using the 'aws-resource-validator-servicediscovery' package. This tool will allow users to input details of their AWS Service Discovery services, namespaces, and instances, and then validate these against the defined Pydantic v2 models provided by the package. The goal is to ensure that the configuration of AWS Service Discovery resources adheres to best practices and is free from common errors.

### Features:
- **Resource Input**: Allow users to input details of AWS Service Discovery services, namespaces, and instances through the command line.
- **Validation**: Use the Pydantic v2 models from 'aws-resource-validator-servicediscovery' to validate the inputted resource configurations.
- **Error Reporting**: Provide clear and concise error messages if any validation fails, indicating which part of the configuration is incorrect.
- **Configuration Saving**: Option to save valid configurations into a file for future reference or deployment.
- **Help Documentation**: Include a help option that provides instructions on how to use the tool and format the input data correctly.

### Steps to Create the Application:
1. **Set Up Environment**: Install Python and necessary packages including 'aws-resource-validator-servicediscovery'.
2. **Define CLI Interface**: Use argparse or a similar library to define command-line arguments for specifying AWS Service Discovery resources.
3. **Input Validation Logic**: Implement logic to parse the command-line inputs and validate them against the Pydantic models from 'aws-resource-validator-servicediscovery'.
4. **Error Handling**: Develop error handling mechanisms to manage invalid inputs gracefully, providing meaningful feedback to the user.
5. **Output Management**: Decide how to present validation results to the user (e.g., console output, saved files).
6. **Testing**: Write tests to ensure your tool works as expected under various scenarios.
7. **Documentation**: Prepare documentation that explains how to install and run the tool, along with examples.

This project aims to streamline the process of validating AWS Service Discovery configurations, ensuring they are set up correctly before deployment.

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