afwf_offer_forge

v0.1.2 safe
4.0
Medium Risk

An example project generated by cookiecutter-pywf_open_source.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk with no network calls or obfuscation, and no signs of credential harvesting. The slight increase in metadata risk due to missing author information and limited package association does not indicate a supply-chain attack.

  • No network calls detected.
  • Subprocess calls present but for benign purposes.
  • Missing author information in metadata.
Per-check LLM notes
  • Network: No network calls detected, which is normal and not suspicious.
  • Shell: Subprocess calls are used for local operations like running tests, which is common but should be monitored to ensure no unintended actions are taken.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package has a missing author and a single associated package, suggesting it may be newly created or abandoned.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • _cwd(Path(root_dir)): subprocess.run(args) def run_cov_test( script: str, module: str,
  • _cwd(Path(root_dir)): subprocess.run(args) if preview: # pragma: no cover platform =
  • e NotImplementedError subprocess.run([open_command, f"{Path(htmlcov_dir).joinpath('index.html')}"
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: easyscalecloud.com>

✓ 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 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 afwf_offer_forge 
Your task is to develop a fully-functional mini-app that leverages the 'afwf_offer_forge' package, which is an example project generated by cookiecutter-pywf_open_source. This app will serve as a tool for generating personalized offer letters for new employees in a company. The goal is to streamline the process of creating these documents, ensuring they are accurate and consistent across all hires.

### Application Overview:
- **Name**: Offer Letter Generator
- **Purpose**: To automate the generation of customized offer letters based on user input.
- **Features**:
  1. User-friendly interface for entering employee details such as name, position, salary, start date, etc.
  2. Integration with 'afwf_offer_forge' to dynamically generate the offer letter content based on the provided data.
  3. Support for multiple templates (e.g., different departments may have slightly varied formats).
  4. Ability to preview the generated offer letter before finalizing it.
  5. Option to save and download the finalized offer letter in PDF format.

### Utilizing 'afwf_offer_forge':
- Use the 'afwf_offer_forge' package to handle the template rendering and customization processes. Ensure that the package is integrated seamlessly into your application, allowing for dynamic content insertion and formatting according to predefined templates.
- Explore the capabilities of 'afwf_offer_forge' to enhance the document generation workflow, such as customizing styles, adding watermarks, or embedding digital signatures.

### Steps to Develop the Application:
1. Set up the development environment, including installing necessary dependencies like 'afwf_offer_forge'.
2. Design the user interface for collecting employee information. Consider using a web framework like Flask or Django for building the front-end.
3. Implement the backend logic to process the form data and pass it to 'afwf_offer_forge' for template rendering.
4. Integrate functionality to allow users to select from different offer letter templates.
5. Add a preview feature that shows the formatted offer letter before it is finalized.
6. Implement the saving and downloading functionality, converting the rendered letter into a PDF file.
7. Test the application thoroughly to ensure all features work correctly and that the generated offer letters are accurate and professional.
8. Document the code and provide clear instructions for deploying the application.