🤖 AI Analysis

Final verdict: SAFE

The package has low risks across all categories except metadata, where there are some concerns about the activity level and maintainer details. However, these factors alone do not conclusively indicate malicious intent or a supply-chain attack.

No network calls detected
No shell execution patterns detected
No obfuscation or credential harvesting patterns detected
Potential low activity and lack of maintainer details

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of potential low activity and lack of maintainer details, which could indicate a risk.

🔬 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 score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ 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 Refined-Augment

Create a fun and interactive augmented reality (AR) app using the Python package 'Refined-Augment'. Your goal is to develop a mini-app that detects faces in real-time using a webcam and overlays customizable AR objects such as hats, glasses, or mustaches above the detected faces. The app should allow users to switch between different AR objects and adjust their size and position relative to the detected faces.

Step-by-Step Guide:
1. Set up your development environment by installing Python and the necessary libraries, including 'Refined-Augment'.
2. Initialize the app to capture video from a webcam.
3. Use 'Refined-Augment' to detect faces in real-time within the captured video feed.
4. Define a set of pre-designed AR objects (e.g., hats, glasses, mustaches).
5. Implement functionality to overlay these AR objects on top of the detected faces.
6. Add controls to allow users to switch between different AR objects and adjust their size and position.
7. Ensure the app runs smoothly and responsively, providing a seamless user experience.
8. Optionally, include features like saving screenshots or recording videos of the augmented faces.

Suggested Features:
- A variety of AR objects to choose from.
- Real-time adjustment of AR object size and position.
- User interface to select and control AR objects.
- Option to save augmented frames or record augmented videos.
- Compatibility with multiple webcam resolutions and frame rates.

How 'Refined-Augment' is Utilized:
- 'Refined-Augment' will handle the face detection process, identifying the location and boundaries of faces in the video feed. Once faces are detected, your app will use this information to accurately place and scale the AR objects over the detected faces.
- Additionally, 'Refined-Augment' may provide tools or methods for optimizing performance, ensuring that the app remains responsive even when running on less powerful hardware.