AI Analysis
Final verdict: SAFE
The package exhibits benign behavior with no network calls, shell executions, or obfuscation techniques. However, the incomplete author information and possibly inactive account contribute to a slightly elevated metadata risk.
- No network calls
- Incomplete author information
Per-check LLM notes
- Network: No network calls suggest normal behavior for a utility-focused package.
- Shell: No shell execution patterns indicate the package does not perform system-level operations.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
- Metadata: The author information is incomplete and the account seems new or inactive, raising some concerns but not definitive signs of 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 (297 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-config
Create a mini-application called 'AWS Config Validator' using Python that leverages the 'aws-resource-validator-config' package to validate AWS resource configurations against predefined schemas. This tool should allow users to input their AWS resource configurations in YAML format and then check if these configurations adhere to best practices and standards as defined by the provided schemas from the 'aws-resource-validator-config' package. Step 1: Set up the project environment by installing necessary dependencies including 'aws-resource-validator-config', 'pydantic', and 'PyYAML'. Step 2: Define a class within your application that loads a YAML file containing AWS resource configurations. This class should also handle any exceptions that might arise during the loading process, such as file not found errors or syntax errors in the YAML file. Step 3: Implement a validation function that uses the Pydantic models provided by 'aws-resource-validator-config' to validate the loaded YAML configurations. This function should return a detailed report indicating which resources pass validation and which fail, along with specific reasons for failure. Step 4: Extend the application by adding a feature that allows users to specify custom validation rules or schemas in addition to the ones provided by 'aws-resource-validator-config'. These custom schemas should also be validated using Pydantic models. Step 5: Integrate logging into your application so that every operation, including successful validations and errors, is logged for future reference. Step 6: Develop a user-friendly command-line interface (CLI) for interacting with your application. Users should be able to run the validator on their configuration files directly from the terminal, with options to specify input files, output formats, and verbosity levels. Suggested Features: - Support for multiple AWS resource types (e.g., S3 buckets, EC2 instances). - Option to automatically correct minor issues in the configurations (if applicable). - Integration with popular cloud management tools like Terraform or AWS CloudFormation. - Detailed documentation and examples for common use cases.
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