aws-resource-validator-mediastore

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no signs of direct malicious intent such as network calls, shell execution, or credential harvesting. However, the incomplete author details and the possibility of an inactive user raise concerns about its provenance and maintainability.

  • Incomplete author details
  • Possibly inactive user
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 of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of unauthorized access to credentials.
  • Metadata: The author's details are incomplete, and they seem to be a new or inactive user, which could indicate potential risk.

📦 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 (309 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-mediastore 
Create a Python-based command-line utility named 'MediaStoreInspector' that leverages the 'aws-resource-validator-mediastore' package to validate and inspect Amazon MediaStore resources. This utility should allow users to perform several actions including listing all MediaStore containers, validating container configurations against predefined schemas, and checking for potential issues such as overly permissive access policies.

Steps to develop this utility:
1. Set up a virtual environment and install necessary packages, including 'aws-resource-validator-mediastore', 'boto3' for AWS SDK, and 'typer' for CLI development.
2. Define functions to authenticate with AWS using IAM roles or access keys.
3. Implement a function to list all MediaStore containers within a specified region.
4. Use 'aws-resource-validator-mediastore' to define validation schemas for different aspects of MediaStore containers, such as storage capacity, access permissions, and encryption settings.
5. Create a feature that allows users to input container names and validates their configurations against the defined schemas.
6. Develop a warning system that alerts users if any potential security or performance issues are detected in the container configurations.
7. Ensure the utility outputs results in a human-readable format and supports JSON export for further analysis.
8. Add comprehensive help documentation and examples to guide users through common tasks.
9. Test the utility thoroughly with various AWS accounts and configurations to ensure reliability.
10. Publish the utility on GitHub with clear installation instructions and usage examples.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!