aws-resource-validator-translate

v2.0.3 suspicious
4.0
Medium Risk

Pydantic v2 models for AWS translate, 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 calls, shell execution, obfuscation, and credential harvesting. However, the metadata risk score is moderately high due to incomplete author information and a potentially inactive or new account, raising concerns about potential supply-chain risks.

  • Incomplete author information
  • Potentially inactive/new account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not pose a risk for stealing secrets or credentials.
  • Metadata: The author's information is incomplete and the account seems new or inactive, which raises some suspicion but not enough to conclusively identify 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 (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-translate 
Create a mini-application called 'Translation Validator' that leverages the 'aws-resource-validator-translate' package to validate and manage translations using Amazon Translate service. This application will serve as a tool for developers and content managers to ensure their translation requests meet specific criteria before being processed. Here’s a detailed breakdown of the steps and features for your project:

1. **Setup**: Install the required packages including 'aws-resource-validator-translate', boto3 (for AWS SDK), and pydantic.
2. **Model Definition**: Define input models using the 'aws-resource-validator-translate' package to validate source and target languages, text length, and other parameters relevant to translation requests.
3. **Validation Logic**: Implement validation logic to check if the translation request meets the predefined criteria. Use the defined models from step 2 to perform these validations.
4. **Translation Service Integration**: Integrate the application with Amazon Translate to actually perform the translations after validation. Ensure that only validated requests are sent to the service.
5. **User Interface**: Develop a simple command-line interface (CLI) for users to interact with the application. They should be able to input their text and select source/target languages through this CLI.
6. **Feedback Mechanism**: Provide feedback to users based on the validation results. If a request fails validation, specify why it failed. If successful, display the translated text.
7. **Logging and Error Handling**: Implement logging for all actions performed by the application and handle potential errors gracefully.
8. **Testing**: Write tests to ensure that the validation logic works correctly and that the application handles various scenarios effectively.

This project aims to streamline the process of managing translation requests, ensuring they are both valid and efficiently processed, thereby enhancing user experience and data integrity.

💬 Discussion Feed

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