appligator

v0.1.1 suspicious
4.0
Medium Risk

An application package bundler

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some red flags including shell execution and an incomplete maintainer profile, but lacks evidence of malicious intent such as network calls, obfuscation, or credential harvesting.

  • shell risk due to potential Docker management
  • metadata risk due to incomplete maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is low risk.
  • Shell: Detection of shell execution suggests the package may have functionality related to Docker management, but requires further investigation to ensure it's not being used maliciously.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The maintainer has a new or inactive account and lacks a full author name, which could indicate potential risk.

📦 Package Quality Overall: Medium (5.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://eo-tools.github.io/eozilla
  • Detailed PyPI description (1038 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
  • 27 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in eo-tools/eozilla
  • 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 score 2.0

Found 1 shell execution pattern(s)

  • rror("docker not found") subprocess.check_call( # noqa: S603 [docker_path, "build", "-t", image_na
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository eo-tools/eozilla 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 appligator 
Create a mini-application called 'QuickDeploy' that leverages the 'appligator' package to bundle and deploy small Python applications quickly and efficiently. This application will streamline the process of packaging your Python code into standalone executables that can be run on any system without requiring the user to install Python or any dependencies manually.

Step 1: Define the Scope
- QuickDeploy should allow users to select a directory containing their Python application.
- It should automatically detect and include all necessary dependencies specified in a requirements.txt file within the selected directory.
- The application should bundle these components into a single executable file using the 'appligator' package.

Step 2: User Interface Design
- Develop a simple graphical user interface (GUI) using a library like PyQt5 or Tkinter.
- The GUI should provide options for selecting the source directory and specifying an output path for the bundled executable.
- Include a progress bar to show the bundling process status.

Step 3: Implement Core Functionality
- Utilize the 'appligator' package to handle the bundling process.
- Integrate error handling to manage issues such as missing files or incorrect paths.
- Ensure the bundled executable includes all necessary libraries and runs seamlessly on target systems.

Step 4: Additional Features
- Implement a feature to automatically create a README file detailing how to run the bundled application.
- Add an option to compress the bundled application into a .zip file for easy distribution.
- Include a checksum verification mechanism to ensure the integrity of the bundled application during download.

Step 5: Testing and Deployment
- Thoroughly test the application on different operating systems to ensure compatibility.
- Create a setup.py script for distributing QuickDeploy via PyPI.
- Document the installation and usage instructions clearly.

💬 Discussion Feed

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