attack-on-domain

v0.0.10 suspicious
6.0
Medium Risk

DDD building blocks: entities, value objects, bounded contexts, and validation helpers.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk in terms of network usage, shell execution, and code obfuscation. However, the metadata risk score is elevated due to missing repository information and the maintainer having only one package, which could indicate a potential supply-chain attack.

  • Metadata risk score is high due to missing repository
  • Maintainer has only one package listed
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interaction for its functionality.
  • Shell: No shell execution detected, reducing the risk of unauthorized system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive data being stolen.
  • Metadata: The repository is not found, and the maintainer has only one package which raises suspicion.

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (570 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 83 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 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

No author email provided

Suspicious Page Links

All external links appear legitimate

Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Alfonso Cuesta" 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 attack-on-domain
Develop a fully functional mini-application named 'DomainWarrior' using the Python package 'attack-on-domain'. DomainWarrior is designed to manage different domains of knowledge within a company, ensuring each domain is well-defined and isolated from others. This application will help in organizing and validating data across various business contexts, making it easier to manage complex systems.

### Features:
1. **Domain Definition**: Allow users to define their own domains (e.g., HR, Finance, Sales), each with its own set of rules and validations.
2. **Entities Management**: Within each domain, users can define entities (e.g., Employee in HR, Invoice in Finance) along with their attributes and relationships.
3. **Value Objects**: Users can create value objects that represent meaningful values in their domains (e.g., Currency, DateRange).
4. **Bounded Contexts**: Ensure that each domain is treated as a bounded context, meaning that it has its own model and rules that are not influenced by other domains.
5. **Validation Helpers**: Implement robust validation mechanisms for entities and value objects based on user-defined rules.
6. **User Interface**: Provide a simple and intuitive command-line interface for adding, modifying, and querying domains, entities, and value objects.
7. **Documentation and Help**: Include comprehensive documentation and help options within the application.

### Utilizing 'attack-on-domain':
- Use the package's entity and value object classes to define your custom domain-specific models.
- Leverage the validation helpers provided by 'attack-on-domain' to enforce business rules and ensure data integrity.
- Apply the concept of bounded contexts to isolate domain definitions and prevent conflicts between different areas of the business.

### Steps to Develop DomainWarrior:
1. **Setup Project**: Initialize a new Python project and install the 'attack-on-domain' package.
2. **Define Domains**: Create classes representing different domains using 'attack-on-domain' features.
3. **Manage Entities and Value Objects**: Define entities and value objects within each domain, utilizing the package's capabilities.
4. **Implement Validation**: Set up validation rules for entities and value objects to maintain data consistency.
5. **Build UI**: Develop a command-line interface for interacting with the application.
6. **Testing**: Write tests to ensure that all functionalities work as expected.
7. **Documentation**: Prepare documentation detailing how to use the application and customize it for specific needs.
8. **Deployment**: Package the application for easy distribution and deployment.

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