aws-resource-validator-auditmanager

v2.0.3 safe
3.0
Low Risk

Pydantic v2 models for AWS auditmanager, shipped as a PEP 420 namespace extension of aws-resource-validator.

🤖 AI Analysis

Final verdict: SAFE

The package presents minimal risks based on the analysis, with no indications of malicious activities such as network calls, shell executions, obfuscations, or credential harvesting.

  • Low risk scores across all categories except metadata.
  • Metadata risk due to a new or inactive maintainer account and lack of proper author identification.
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 maintainer has a new or inactive account and lacks a proper author name, which could indicate potential issues.

📦 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_validator
  • Small 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 short
  • Author "" 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-auditmanager 
Your task is to create a Python-based utility named 'AuditChecker' which leverages the 'aws-resource-validator-auditmanager' package to validate and audit AWS resources based on predefined compliance standards. This utility should be designed to help DevOps engineers ensure their AWS environments meet specific security and governance criteria efficiently. Here are the key functionalities your application should include:

1. **Resource Validation**: Implement a feature that allows users to input details of their AWS resources (e.g., S3 buckets, IAM roles, etc.). Using the Pydantic v2 models provided by 'aws-resource-validator-auditmanager', the utility will validate these resources against a set of pre-defined rules.

2. **Compliance Audit**: Extend the validation feature to perform compliance audits. Users should be able to specify a compliance standard (e.g., PCI DSS, HIPAA, etc.), and the utility will check if the resources comply with the chosen standard using the audit manager capabilities embedded within the 'aws-resource-validator-auditmanager'.

3. **Report Generation**: After performing the validation and audit, the utility must generate a comprehensive report detailing any non-compliance issues found during the process. This report should be in a structured format like JSON or CSV for easy review and action.

4. **User Interface**: While primarily command-line driven, consider adding a simple web interface using Flask or Django for easier interaction, especially for non-technical users.

5. **Integration with AWS SDKs**: Ensure that the utility integrates seamlessly with other AWS SDKs to fetch resource details directly from AWS services, thereby reducing manual input errors.

To utilize the 'aws-resource-validator-auditmanager' package effectively, focus on leveraging its Pydantic v2 models to define and enforce validation rules. These models should map directly to the AWS resources being audited, ensuring accurate and consistent validation checks across different types of resources. Additionally, explore how you can extend these models to support new compliance standards as they evolve.

💬 Discussion Feed

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