aws-resource-validator-appfabric

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk in terms of network, shell, and obfuscation activities, but the incomplete author information and apparent inactivity of the maintainer raise concerns about potential supply-chain risks.

  • Incomplete maintainer's author information
  • Maintainer appears to be new or inactive
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of secrets.
  • Metadata: The maintainer's author information is incomplete and they appear to be new or inactive, which raises some suspicion but not enough to conclusively indicate 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 (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-appfabric 
Your task is to develop a command-line utility named 'AWS AppFabric Validator' using Python. This tool will leverage the 'aws-resource-validator-appfabric' package to validate and ensure the integrity of AWS AppFabric resources defined in YAML configuration files. Your goal is to create a robust, user-friendly tool that not only validates configurations but also provides meaningful feedback to help users correct any issues found.

Step-by-Step Instructions:
1. Begin by setting up a virtual environment and installing the necessary dependencies, including 'aws-resource-validator-appfabric'.
2. Design the structure of your application to include modules for reading YAML files, validating the content against Pydantic models from 'aws-resource-validator-appfabric', and outputting validation results.
3. Implement functionality to parse YAML files containing AWS AppFabric resource definitions. These files should follow a standard structure, allowing for easy parsing and validation.
4. Utilize Pydantic models from 'aws-resource-validator-appfabric' to validate the parsed data. Ensure that each model accurately reflects the schema of corresponding AWS AppFabric resources.
5. Develop a feature that generates detailed error messages for invalid configurations, guiding users on how to correct their YAML files.
6. Add an option for the utility to automatically correct minor issues in the YAML files, such as fixing typos in resource names or adjusting indentation.
7. Integrate logging capabilities to track validation processes and errors, which can be useful for debugging and auditing purposes.
8. Finally, implement a user-friendly CLI interface that allows users to specify YAML files for validation, view validation results, and optionally save corrected versions of their files.

Suggested Features:
- Support for multiple YAML files in a single run.
- Detailed logging of all validation activities.
- Interactive mode where users can be prompted for corrections if issues are found.
- Compatibility checks between different AWS services used in the AppFabric configuration.
- Extensibility to support additional AWS AppFabric resource types beyond those initially implemented.

By following these steps and incorporating the suggested features, you'll create a valuable tool for developers and DevOps engineers working with AWS AppFabric, ensuring their configurations are accurate and adhere to best practices.

💬 Discussion Feed

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