🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks due to shell execution capabilities and an inactive maintainer, but there's no strong evidence of malicious intent. Further investigation is recommended.

High Shell risk
Inactive maintainer

Per-check LLM notes

Network: No network calls detected, indicating low risk.
Shell: Multiple instances of shell execution may indicate functionality for running system commands, which could be legitimate but also poses a higher risk for potential misuse.
Obfuscation: The observed import patterns are likely used for dynamic module loading rather than malicious obfuscation.
Credentials: No suspicious patterns related to credential harvesting were detected.
Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

try: m = __import__(mod, fromlist=['pyqtBoundSignal', 'QMetaMethod']) if hasattr(m, "pyqtBoundSignal"):
try: m = __import__(mod, fromlist=['SignalInstance', 'QMetaMethod']) if hasattr(m, "SignalInstance"):

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

try: out = subprocess.run( cmd, shell=True, capture_output=True, text=
= [] try: proc = subprocess.run( ["grep", "-RnE", GREP_REGEX, "src"],
_quote(cmd)}'" proc = subprocess.run(full, shell=True, capture_output=True, text=True) re
r.""" try: proc = subprocess.run(["bash", "-lc", cmd], cwd=path, capture_output=True, text=Tr
ess.run( cmd, shell=True, capture_output=True, text=True, check=True ).s
proc = subprocess.run(full, shell=True, capture_output=True, text=True) return (proc.stdou

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: abstractendeavors.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 2.0

1 maintainer concern(s) found

Author "putkoff" 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 abstract-gui

Create a fully-functional task manager application using the 'abstract-gui' package. This application will allow users to manage their tasks effectively, including adding new tasks, marking tasks as completed, deleting tasks, and viewing task details. Additionally, the app should support categorization of tasks into different categories such as Work, Personal, etc., and allow users to filter tasks based on these categories.

The application should utilize the following core features of the 'abstract-gui' package:
- Reusable components for building the UI, such as buttons, lists, and input fields.
- Factories for easily creating instances of these components.
- Utilities for logging actions performed within the application, which will help in debugging and understanding user interactions.
- Threading utilities to ensure the application remains responsive even when performing time-consuming operations like saving data to disk.
- State management capabilities to maintain the current state of the application, including the list of tasks and the currently selected category.

Step-by-step instructions for the application development are as follows:
1. Set up the initial environment, including installing the 'abstract-gui' package and any other necessary dependencies.
2. Design the main layout of the application, incorporating components from 'abstract-gui' for task listing, task creation, and category filtering.
3. Implement functionality for adding new tasks, ensuring that the user interface updates immediately after a new task is added.
4. Add the ability to mark tasks as completed and delete tasks, updating the UI accordingly.
5. Integrate state management to keep track of the tasks and categories, and ensure that changes persist across different sessions.
6. Use threading utilities to handle background operations such as saving tasks to a file, ensuring that the application remains interactive during these processes.
7. Finally, implement logging to record all significant events within the application, providing insights into user behavior and potential issues.

This task manager application will serve as a practical example of how the 'abstract-gui' package can simplify the process of developing complex, feature-rich applications in Python.