aws-resource-validator-billing

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risk indicators but raises suspicion due to incomplete author information and potential lack of activity from the developer.

  • Incomplete author information
  • Potential lack of developer activity
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires them for functionality.
  • Shell: No shell execution detected, which is expected and safe.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is incomplete and they appear to be new or inactive, which raises some suspicion but not enough to conclude malice.

📦 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-billing 
Develop a Python-based utility named 'BillingGuard' which leverages the 'aws-resource-validator-billing' package to monitor AWS billing alerts and validate resource costs against predefined budgets. This tool will help users stay within their budget by providing real-time notifications when spending exceeds certain thresholds.

Steps to complete the project:
1. Set up an AWS account and enable Cost Explorer API access.
2. Install necessary Python packages including 'boto3', 'aws-resource-validator-billing', and any additional libraries needed for notifications.
3. Use Pydantic models from 'aws-resource-validator-billing' to define validation rules based on cost categories like S3 storage, EC2 instances, etc.
4. Implement a function to fetch current month's AWS bill data using Cost Explorer API.
5. Compare fetched data against predefined budgets using the validation rules defined in step 3.
6. If spending exceeds the budget, send a notification via email or SMS.
7. Optionally, integrate a web dashboard using Flask or Django to visualize spending trends and budget compliance.
8. Ensure the application logs all operations for auditing purposes.

Suggested Features:
- Customizable budget limits per service/resource type.
- Historical spending analysis.
- Automated budget adjustment based on historical trends.
- Support for multiple AWS accounts.
- Integration with third-party alerting services like Slack or PagerDuty.

This project aims to demonstrate how the 'aws-resource-validator-billing' package can be effectively utilized to manage and control AWS costs through automated validation and alerting mechanisms.

💬 Discussion Feed

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