aws-resource-validator-account

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks in terms of network, shell, obfuscation, and credential handling. However, the incomplete maintainer's author information and the possibility of a new or inactive account increase the overall risk level.

  • Incomplete maintainer's author information
  • Possibly new or inactive maintainer account
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 suspicious system command executions.
  • Obfuscation: No obfuscation patterns detected, indicating a low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
  • Metadata: The maintainer's author information is incomplete, and the account seems new or inactive, raising some suspicion but not enough to conclusively identify it as malicious.

📦 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_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-account 
Create a Python-based command-line tool that validates and manages AWS accounts using the 'aws-resource-validator-account' package. This tool will allow users to validate AWS account configurations against predefined schemas, ensuring compliance with organizational standards and best practices. Additionally, it should provide functionalities to compare multiple accounts against each other and generate reports summarizing the validation results. Here’s a detailed breakdown of the steps and features:

1. **Setup**: Install the necessary packages including 'aws-resource-validator-account'. Ensure you have the required AWS SDK (boto3) and Pydantic installed.

2. **Account Configuration Validation**: Implement a feature where users can input their AWS account configuration details. Use 'aws-resource-validator-account' to validate these configurations against predefined schemas. These schemas should cover critical aspects such as security settings, access control policies, and resource management.

3. **Comparison Tool**: Develop a module within your tool that allows users to upload multiple AWS account configurations. The tool should then automatically compare these configurations based on specified criteria (e.g., security level, cost optimization strategies). This comparison should highlight discrepancies and suggest improvements.

4. **Reporting**: Integrate a reporting system that generates comprehensive reports summarizing the validation and comparison results. Users should be able to choose between different formats like CSV, JSON, or HTML.

5. **Interactive CLI**: Design an intuitive command-line interface for users to interact with the tool easily. Commands should include options for validating single accounts, comparing multiple accounts, and generating reports.

6. **Customization**: Allow users to customize validation schemas and comparison criteria according to their specific needs. This flexibility ensures the tool remains useful across various organizational contexts.

7. **Security Measures**: Ensure all data exchanges and storage within the tool are secure, especially concerning sensitive information like AWS keys and configuration files.

By following these steps and incorporating these features, your mini-application will serve as a powerful tool for managing and validating AWS accounts efficiently and effectively.

💬 Discussion Feed

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