aws-resource-validator-guardduty

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risk in terms of network and shell activities but raises suspicion due to the lack of detailed maintainer information and an inactive account.

  • Maintainer has a new or inactive account
  • Lack of author information
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package doesn't require external communication.
  • Shell: No shell execution patterns detected, indicating no immediate risk of executing arbitrary commands.
  • Metadata: The maintainer has a new or inactive account and lacks author information, which raises some suspicion but does not definitively indicate malicious activity.

📦 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-guardduty 
Create a Python-based utility named 'GuardDutyAnalyzer' that leverages the 'aws-resource-validator-guardduty' package to validate and analyze AWS GuardDuty findings. This tool should provide developers and security professionals with a simple way to check if their GuardDuty configurations adhere to best practices and standards.

Step 1: Setup
- Install necessary Python packages including 'boto3', 'aws-resource-validator-guardduty', and any other dependencies.
- Configure AWS credentials and ensure access to GuardDuty.

Step 2: Define Validation Rules
- Utilize the Pydantic models provided by 'aws-resource-validator-guardduty' to define a set of validation rules. These rules should cover common aspects such as finding severity levels, types of threats detected, and compliance with organizational policies.

Step 3: Fetch and Parse Data
- Use boto3 to fetch GuardDuty findings from a specified AWS account or region.
- Parse these findings using the Pydantic models to ensure they conform to the defined validation rules.

Step 4: Analyze and Report
- Implement functionality to analyze parsed findings against the validation rules.
- Generate a report detailing which findings comply with the rules and which do not, along with suggestions for remediation.

Suggested Features:
- Interactive CLI interface for ease of use.
- Support for multiple AWS accounts and regions.
- Integration with logging services for tracking analysis results over time.
- Option to export reports in various formats (CSV, JSON).
- Customizable validation rules based on user input.

How 'aws-resource-validator-guardduty' is Utilized:
- The package's Pydantic models will serve as the foundation for defining validation rules. They help ensure that the GuardDuty findings are correctly structured and contain expected fields.
- By leveraging these models, the utility can perform robust validation checks without needing complex parsing logic.
- Additionally, the package's namespace extension feature allows for seamless integration into the utility's codebase, making it easier to extend and maintain.

💬 Discussion Feed

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