AI Analysis
Final verdict: SAFE
The package shows low risks across all evaluated categories with no direct evidence of malicious intent or activity. However, the incomplete author details and single-package maintainer suggest potential inactivity or newness, which slightly elevates the overall risk score.
- No network calls or shell executions detected
- Incomplete author details and single-package maintainer
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 patterns detected, indicating no immediate risk of command injection or unauthorized system access.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author details are incomplete, and the maintainer has only one package, suggesting a potentially new or inactive account which may warrant further investigation.
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-s3files
Create a command-line tool named 'S3Audit' that leverages the 'aws-resource-validator-s3files' package to audit and validate S3 bucket configurations against best practices and compliance standards. This tool will help users ensure their Amazon S3 buckets are secure and compliant with industry regulations. Step 1: Set up your development environment with Python 3.9+ and install necessary packages including 'aws-resource-validator-s3files', 'boto3', and 'click'. Step 2: Define a set of validation rules based on common security and compliance requirements for S3 buckets. These rules should cover aspects like public access, encryption settings, versioning, and server-side encryption. Step 3: Use the 'aws-resource-validator-s3files' package to create Pydantic models that represent these validation rules. Ensure each model accurately reflects the structure and constraints of the corresponding S3 configuration. Step 4: Implement a function within your tool that connects to an AWS S3 bucket using boto3, fetches its current configuration, and validates it against the defined Pydantic models from Step 3. Step 5: Develop a reporting feature that outputs the results of the validation process. This report should clearly indicate which configurations meet the standards and which do not, providing actionable recommendations for improvement. Step 6: Enhance the tool with additional features such as: - Support for multiple S3 buckets at once. - Option to save the audit results to a file. - Periodic scheduling of audits via cron jobs or similar. - Integration with AWS CloudWatch for alerting on non-compliant configurations. Utilize the 'aws-resource-validator-s3files' package extensively throughout your project to ensure that all S3-related data models are robust and adhere strictly to AWS specifications. Your goal is to provide a reliable and easy-to-use tool that helps organizations maintain high standards of data security and compliance.
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