aws-resource-validator-kafkaconnect

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks associated with network, shell, and obfuscation activities. However, the incomplete author information and potentially inactive account increase suspicion, warranting further investigation.

  • Incomplete author information
  • Potentially inactive account
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 direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author information is incomplete and the account seems new or inactive, which raises some concerns but not enough to definitively label it as malicious.

📦 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 (315 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-kafkaconnect 
Create a Python-based utility called 'KafkaConnectHealthChecker' that leverages the 'aws-resource-validator-kafkaconnect' package to validate and monitor the health of Kafka Connect resources in an AWS environment. This tool will serve as a comprehensive health checker for Kafka Connect clusters, ensuring that all components are functioning correctly and meeting the specified validation criteria. Here are the steps and features you need to implement:

1. **Setup and Configuration**: Initialize your project with necessary dependencies including 'aws-resource-validator-kafkaconnect'. Define configuration options for specifying AWS credentials, region, and the Kafka Connect cluster ARN.

2. **Resource Validation**: Use the Pydantic v2 models provided by 'aws-resource-validator-kafkaconnect' to define validation rules for Kafka Connect resources. These rules should cover aspects like connector status, task status, worker health, and any custom configurations defined by the user.

3. **Health Monitoring**: Implement a function to periodically check the Kafka Connect cluster against the defined validation rules. This function should fetch the current state of the Kafka Connect resources from AWS and compare it against the validation criteria.

4. **Alerting System**: Integrate an alerting system within your utility that triggers notifications when a resource fails to meet the validation criteria. Notifications can be sent via email, Slack, or any other preferred communication channel based on user configuration.

5. **User Interface**: Develop a simple command-line interface (CLI) for users to interact with 'KafkaConnectHealthChecker'. This CLI should allow users to configure the tool, run health checks manually, and view the results of these checks.

6. **Logging and Reporting**: Ensure that the utility logs all activities and results for auditing purposes. Additionally, generate periodic reports summarizing the health status of the Kafka Connect cluster over time.

The 'aws-resource-validator-kafkaconnect' package is central to this project as it provides the foundational models and validation logic required to assess the health and compliance of Kafka Connect resources. By leveraging these models, you can ensure that your utility accurately reflects the operational status of the Kafka Connect cluster, helping administrators maintain high standards of reliability and performance.

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