aws-resource-validator-codeguruprofiler

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network, shell, obfuscation, and credential handling, but the metadata risk score is elevated due to sparse author details and a single package from the maintainer.

  • Sparse author details
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, which is expected for a Python package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
  • Metadata: The author details are sparse and the maintainer has a single package, which raises some concerns but does not conclusively indicate malicious intent.

📦 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 (327 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-codeguruprofiler 
Develop a Python-based utility called 'ProfilerGuard' that leverages the 'aws-resource-validator-codeguruprofiler' package to validate AWS CodeGuru Profiler configurations. This tool will serve as a robust pre-deployment check for ensuring that your AWS CodeGuru Profiler resources meet specific criteria and best practices.

### Project Scope:
1. **Configuration Validation**: Create a command-line interface (CLI) that allows users to input their AWS CodeGuru Profiler configuration details (e.g., profiling groups, agents, etc.). The utility should then validate these configurations against predefined rules and best practices using the Pydantic v2 models provided by the 'aws-resource-validator-codeguruprofiler' package.
2. **Rule Engine**: Implement a rule engine that checks for common issues such as misconfigured permissions, missing tags, or unsupported regions. These rules should be customizable via a configuration file.
3. **Report Generation**: After validation, generate a comprehensive report detailing any issues found along with suggestions for remediation. The report should be both human-readable and machine-readable (JSON format).
4. **Integration Testing**: Include a suite of integration tests that use mock data to ensure the utility works as expected under various scenarios.
5. **Documentation**: Provide clear documentation on how to install and use the utility, including examples and best practices for configuring AWS CodeGuru Profiler.

### Utilization of 'aws-resource-validator-codeguruprofiler':
- Use the Pydantic v2 models from the package to define the structure and validation logic for AWS CodeGuru Profiler configurations.
- Leverage the package's namespace extension capabilities to ensure seamless integration with other AWS resource validation tools if needed.
- Customize the validation logic by extending the provided models or adding additional validators based on specific organizational requirements.

This project aims to streamline the process of deploying and managing AWS CodeGuru Profiler resources while adhering to best practices, thereby reducing the likelihood of configuration errors and improving overall security and performance.

💬 Discussion Feed

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