aws-resource-validator-s3tables

v2.0.3 suspicious
5.0
Medium Risk

Pydantic v2 models for AWS s3tables, shipped as a PEP 420 namespace extension of aws-resource-validator.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risk scores for network, shell, obfuscation, and credential risks, but the maintainer's author name is missing, and there's no activity or history, which raises concerns about potential supply-chain attacks.

  • Missing maintainer information
  • No activity or history from the maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package that does not require 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's author name is missing and they appear to be new or inactive, raising some suspicion.

📦 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 (303 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-s3tables 
Create a Python-based command-line utility named 'S3TableChecker' that leverages the 'aws-resource-validator-s3tables' package to validate the structure and integrity of Amazon S3 tables. This utility will help users ensure their S3 table configurations adhere to best practices and standards, preventing common errors and inconsistencies.

**Step 1: Setup and Configuration**
- Install necessary Python packages including 'aws-resource-validator-s3tables'.
- Define configuration options for specifying which S3 tables to check and how they should be validated.

**Step 2: Validation Logic**
- Implement validation rules based on the Pydantic models provided by 'aws-resource-validator-s3tables'. These models will serve as templates against which actual S3 table configurations are compared.
- Include checks for common issues such as missing required fields, incorrect data types, and inconsistent naming conventions.

**Step 3: User Interface**
- Design a simple yet effective command-line interface (CLI) for interacting with the tool.
- Allow users to specify input files containing S3 table configurations and output directories for results.

**Step 4: Reporting**
- Develop a reporting system that summarizes validation results, highlighting any issues found during the process.
- Provide options for generating detailed logs and summaries in various formats like JSON or CSV.

**Additional Features (Optional)**
- Support for automated testing of multiple S3 table configurations at once.
- Integration with CI/CD pipelines for continuous validation of S3 table structures.
- Option to automatically correct minor issues identified during validation, with user confirmation before making changes.

This project aims to streamline the process of validating S3 table configurations, ensuring they meet predefined standards and reducing the likelihood of deployment failures due to configuration errors.

💬 Discussion Feed

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