AI Analysis
Final verdict: SAFE
The package has minimal risks with no network calls, shell executions, obfuscations, or credential harvesting attempts. The only elevated risk is metadata-related due to incomplete author information.
- Low network risk
- No shell execution detected
- No obfuscation techniques observed
- Incomplete author metadata
Per-check LLM notes
- Network: No network calls detected, which is normal for packages not requiring external API interactions.
- Shell: No shell execution patterns 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 author's information is incomplete and they may be new or inactive, but no other suspicious flags were raised.
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 (315 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-interconnect
Create a Python-based utility named 'InterConnectInspector' that leverages the 'aws-resource-validator-interconnect' package to validate AWS Direct Connect Interconnect configurations. This tool will help network administrators ensure their interconnects are correctly configured according to AWS best practices and standards. Here’s a detailed plan on how to build this utility: 1. **Setup Project**: Initialize a new Python project using pipenv or virtualenv. Install necessary packages including 'aws-resource-validator-interconnect', 'boto3' (for AWS SDK), and 'pydantic'. 2. **Configuration Loading**: Design a function to load configuration details from a YAML file or environment variables. These configurations will include AWS credentials, region, and specific details about the interconnects to be validated. 3. **Validation Logic**: Use the 'aws-resource-validator-interconnect' package to define validation rules based on Pydantic models. Implement functions to check if the provided interconnect configurations comply with these rules. For instance, validate attributes like bandwidth, partnerName, and vlan. 4. **Integration with AWS**: Utilize 'boto3' to interact with AWS services. Write functions that fetch live data from AWS Direct Connect APIs to compare against the validated configurations. Ensure that the fetched data matches the expected values defined in your validation logic. 5. **Report Generation**: Develop a feature to generate a comprehensive report detailing any discrepancies found between the provided configurations and AWS live data. This report should be easily readable and exportable as a PDF or HTML document. 6. **User Interface**: Although not mandatory, consider adding a simple command-line interface (CLI) for users to input configuration files, run validations, and view reports directly from the terminal. 7. **Testing & Documentation**: Write unit tests for each part of your code to ensure reliability. Provide thorough documentation explaining how to install, configure, and use 'InterConnectInspector'. Include examples of valid and invalid configurations for testing purposes. By completing this project, you'll have a robust tool for validating AWS Direct Connect Interconnect configurations, ensuring they meet necessary standards and best practices.
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