🤖 AI Analysis

Final verdict: SAFE

The package shows very low risks across all technical indicators except metadata, where there is some uncertainty due to limited information about the author. Overall, it appears safe, but further monitoring or investigation into the author's background may be warranted.

No network calls
No shell execution
No obfuscation
No credential harvesting
Limited author information

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 direct system command execution.
Obfuscation: No obfuscation patterns detected, suggesting low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is new with limited information about the author, raising some suspicion but not conclusive evidence of malice.

🔬 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: abstractcore.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository lpalbou/AbstractFramework appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
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 abstractvideo

Your task is to create a simple yet powerful video editing mini-application using the 'abstractvideo' package, which is part of the larger AbstractFramework suite designed for AI-driven video processing. This application will serve as a user-friendly interface for basic video manipulation tasks such as cropping, resizing, and applying filters. Additionally, it should support more advanced features like object detection and scene recognition based on AI models integrated within the 'abstractvideo' package.

Step 1: Begin by setting up your development environment. Ensure you have Python installed along with the necessary libraries including 'abstractvideo'.

Step 2: Design the user interface for your application. It should allow users to upload a video file from their local machine. Provide options for selecting different video processing actions (e.g., crop, resize, apply filter).

Step 3: Implement the core functionality for each selected action using the 'abstractvideo' package. For example, use the package's cropping module to allow users to specify coordinates for cropping the video.

Step 4: Add advanced features utilizing AI capabilities provided by 'abstractvideo'. Enable users to perform object detection within their videos and highlight detected objects with bounding boxes. Similarly, implement scene recognition to categorize scenes in the video into predefined categories (e.g., indoor, outdoor, night-time).

Step 5: Integrate error handling and user feedback mechanisms to ensure a smooth user experience. Display informative messages when operations succeed or fail.

Step 6: Test your application thoroughly with various types of input videos to ensure robustness and reliability.

Suggested Features:
- User-friendly drag-and-drop video upload feature.
- Real-time preview of video transformations before finalizing edits.
- Option to save edited videos locally or share them directly via social media platforms.
- Support for multiple video formats.
- Detailed documentation explaining how to use the application and customize it further.