AI Analysis
Final verdict: SUSPICIOUS
The package presents minimal risks based on current analysis but raises suspicion due to the maintainer's new or inactive account and lack of detailed author information.
- Low network, shell, obfuscation, and credential risks.
- Maintainer has a new or inactive account with insufficient author details.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external API interactions.
- Shell: No shell execution detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has a new or inactive account and lacks detailed author information, which may indicate potential risk.
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 (300 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_validatorSmall 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 shortAuthor "" 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-appsync
Your task is to create a command-line utility that validates AWS AppSync resources using the 'aws-resource-validator-appsync' Python package. This utility will help developers ensure their AWS AppSync configurations comply with best practices and adhere to specific validation rules. Here’s a detailed breakdown of what your utility should accomplish: 1. **Resource Validation**: Implement functionality that reads an AWS AppSync configuration file (in JSON format) and validates it against predefined Pydantic models provided by the 'aws-resource-validator-appsync' package. The validation process should check for common issues such as missing fields, incorrect data types, and compliance with AWS AppSync schema requirements. 2. **Custom Validation Rules**: Allow users to define custom validation rules through a configuration file. These rules can specify additional checks beyond what the default Pydantic models provide, such as ensuring certain fields contain specific values or patterns. 3. **Error Reporting**: When validation fails, your utility should generate a detailed report listing all errors found in the configuration file. Each error should include a description of the issue, the location within the file where the problem was detected, and suggestions on how to fix it. 4. **Integration with AWS CLI**: Enable seamless integration with the AWS Command Line Interface (CLI) so that users can directly validate AppSync configurations from their AWS environments without needing to manually export files. 5. **User-Friendly Interface**: Design a simple and intuitive command-line interface for interacting with your utility. Commands should allow users to run validations, view reports, and manage custom validation rules easily. 6. **Documentation and Examples**: Provide comprehensive documentation detailing how to use your utility effectively. Include examples of common validation scenarios and how to handle typical configuration issues. To achieve these goals, you will need to leverage the 'aws-resource-validator-appsync' package to load and validate AWS AppSync configurations. Additionally, consider incorporating other Python libraries such as 'pyyaml' for parsing configuration files and 'click' for building a user-friendly command-line interface.
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