AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity based on the provided analysis notes. It does not make network calls, execute shell commands, or use obfuscation techniques.
- No network risk
- No shell risk
- No obfuscation risk
- No credential risk
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access to function.
- Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, suggesting legitimate code.
- Credentials: No credential harvesting patterns detected, indicating safe handling of secrets.
- Metadata: The maintainer's author name is missing or very short and has only one package, indicating a potentially new or less active account.
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 (318 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-iot-jobs-data
Create a Python-based utility named 'IoTJobValidator' that leverages the 'aws-resource-validator-iot-jobs-data' package to validate and manage IoT Jobs data for AWS IoT Core. This tool should provide developers and system administrators with an easy-to-use interface to ensure that their IoT Jobs configurations adhere to best practices and AWS standards. Step 1: Set Up Your Environment - Install Python and necessary libraries including 'aws-resource-validator-iot-jobs-data'. - Ensure you have AWS credentials configured for accessing IoT Jobs resources. Step 2: Design the Main Functionality - Implement a function to fetch IoT Job documents from AWS IoT Core. - Utilize the Pydantic models provided by 'aws-resource-validator-iot-jobs-data' to validate these documents against predefined schemas. - Provide feedback on validation results, indicating which fields are missing or incorrectly formatted. Step 3: Add Optional Features - Integrate a feature to automatically correct minor issues found during validation if possible. - Include a reporting module that generates detailed logs of all validation activities for auditing purposes. - Offer support for batch processing, allowing users to validate multiple jobs at once. Step 4: User Interface - Develop a simple command-line interface (CLI) for interacting with the utility. - Optionally, create a web-based interface using Flask or Django for more interactive user experience. Step 5: Documentation and Testing - Write comprehensive documentation detailing installation, configuration, and usage instructions. - Implement unit tests to ensure the reliability and robustness of your utility. How 'aws-resource-validator-iot-jobs-data' Package is Utilized: - Import Pydantic models from the package to define expected structure of IoT Job documents. - Use these models to validate fetched job data ensuring it conforms to AWS specifications. - Handle exceptions gracefully when invalid data is encountered, providing meaningful error messages.
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