🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to its use of shell commands, which can be legitimate but may also indicate potential misuse. There are no clear signs of malicious intent, but the low engagement and poor metadata quality raise some concerns.

Shell risk due to execution of shell commands
Low engagement and poor metadata quality

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: The package attempts to execute shell commands, which could be used for legitimate purposes like installing dependencies but also raises suspicion for potential misuse or malicious activities.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
Metadata: The package shows low engagement and poor metadata quality, but there are no clear signs of malicious intent.

🔬 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)

lf): try: subprocess.run(['pip', 'install', 'docker'], encoding='utf-8') exce
try: result = subprocess.run(cmd, capture_output=True, text=True, check=True)
t): try: result = subprocess.run(command, text=True, stdout=subprocess.PIPE) if resul

✓ 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

Repository kalterBebapKacke/SubTextHighlight appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with SubTextHighlight

Create a mini-application named 'SubtitleEnhancer' using Python, which leverages the 'SubTextHighlight' package to generate, format, and enhance subtitles for video files. The application should allow users to input a video file and a subtitle file (in SRT format), and then apply various enhancements to the subtitles based on user preferences. Here are the steps and features to include:

1. **User Interface**: Develop a simple and intuitive graphical user interface (GUI) using Tkinter. The GUI should allow users to select a video file and a subtitle file (.srt).
2. **Loading Files**: Implement functionality to load both the video and subtitle files into the application.
3. **Enhancement Options**:
   - **Font Style**: Allow users to choose from different font styles (e.g., Arial, Times New Roman).
   - **Font Size**: Provide options to increase or decrease the font size of the subtitles.
   - **Background Color**: Enable customization of the background color behind the subtitles.
   - **Outline**: Add an option to enable or disable an outline around the subtitles.
4. **Preview Functionality**: Include a preview feature where users can see how their selected enhancements will look on the video without saving any changes.
5. **Save Enhancements**: After reviewing the preview, users should have the ability to save their enhanced subtitle file in a new SRT format.
6. **Help Documentation**: Integrate a help section within the GUI that explains each enhancement option and provides examples.

The 'SubTextHighlight' package should be utilized to handle the parsing, formatting, and rendering of the subtitle text. Ensure that the application is robust, error-free, and user-friendly.