aws-resource-validator-rum

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious behavior, but the maintainer's incomplete and possibly inactive profile raises concerns about potential supply-chain risks.

  • Metadata risk due to incomplete maintainer profile
  • Maintainer may be new or inactive
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The maintainer has an incomplete profile and appears to be new or inactive, which raises some suspicion but does not conclusively indicate malicious intent.

📦 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 (288 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-rum 
Create a Python-based command-line utility named 'RUMChecker' that leverages the 'aws-resource-validator-rum' package to validate AWS Resource Usage Monitoring (RUM) configurations for web applications. This tool will help developers and DevOps engineers ensure their RUM configurations adhere to best practices and are correctly set up for optimal performance monitoring.

Steps to implement:
1. Set up a basic command-line interface using Python's argparse module to accept input arguments such as AWS profile name, region, and configuration file path.
2. Integrate the 'aws-resource-validator-rum' package to define validation rules based on Pydantic v2 models provided by the package. These rules should cover essential aspects of RUM configurations like data indexing, data retention periods, and security settings.
3. Develop a function within your utility that reads the specified configuration file and validates it against the defined Pydantic models from 'aws-resource-validator-rum'.
4. Implement error handling to provide meaningful feedback when a configuration fails validation, suggesting possible corrections.
5. Extend the utility to allow for automatic remediation suggestions or even direct modifications to the configuration file if deemed safe and user-consented.
6. Finally, add documentation and usage examples to make it easy for users to integrate 'RUMChecker' into their development workflows.

Suggested Features:
- Support for multiple AWS profiles and regions.
- Interactive mode where users can input configuration details directly through the CLI.
- Integration with popular CI/CD pipelines via environment variables or additional configuration files.
- Detailed logging and reporting capabilities for tracking validation history and trends.

By following these steps and incorporating the suggested features, you'll create a robust and user-friendly tool that significantly enhances the management and validation of AWS RUM configurations.

💬 Discussion Feed

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