aws-resource-validator-discovery

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories with no network calls, shell executions, or obfuscation techniques observed. However, the metadata risk slightly increases due to incomplete maintainer information.

  • Low network and shell risk
  • Incomplete maintainer metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution detected, indicating no immediate risk of command injection or system manipulation.
  • 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 or very short, and they appear to have only one package on PyPI, which may indicate a new or inactive account.

📦 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 (306 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-discovery 
Your task is to develop a Python-based utility named 'AWS Discovery Explorer' that leverages the 'aws-resource-validator-discovery' package to assist DevOps engineers and cloud administrators in validating and discovering AWS resources efficiently. This tool will provide insights into various aspects of AWS resources, such as their compliance with best practices, security status, and cost optimization opportunities.

The application should have the following core functionalities:
1. **Resource Discovery**: Allow users to input specific AWS resource types (e.g., EC2 instances, S3 buckets) and regions, then discover all available resources matching those criteria. Utilize the 'aws-resource-validator-discovery' package to define the schema and validate the discovered resources against predefined rules.
2. **Compliance Check**: Implement a feature to check if the discovered resources comply with common AWS best practices and security standards. For example, ensure that all S3 buckets have server-side encryption enabled and that EC2 instances are using the latest AMIs.
3. **Security Assessment**: Provide a security assessment for each resource, highlighting potential vulnerabilities and suggesting remediation steps. This could include checking if IAM roles are overly permissive, if RDS instances are publicly accessible, etc.
4. **Cost Analysis**: Offer a basic cost analysis feature to estimate monthly costs based on the usage patterns of the discovered resources. Users should be able to see estimated costs for different services and identify cost-saving opportunities.
5. **Reporting**: Generate comprehensive reports summarizing the findings from the discovery, compliance checks, security assessments, and cost analyses. These reports should be exportable in formats like PDF and CSV.

To achieve these goals, you will need to:
- Use the 'aws-resource-validator-discovery' package to define and validate resource schemas.
- Integrate with the AWS SDK for Python (boto3) to interact with AWS APIs.
- Implement a user-friendly command-line interface (CLI) for interacting with the tool.
- Ensure the application is modular and easily extendable for future enhancements.

Additionally, consider adding optional features such as:
- Support for filtering resources based on tags or other metadata.
- Real-time notifications for critical issues identified during the assessment.
- Integration with popular logging frameworks for audit purposes.

Your goal is to create a robust, efficient, and user-friendly tool that significantly simplifies the process of managing and optimizing AWS resources.

💬 Discussion Feed

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