AI Analysis
Final verdict: SUSPICIOUS
The package exhibits a high network risk due to network calls to localhost, which raises concerns about its true purpose. Despite lacking evidence of other malicious activities, the low maintainer activity and poor metadata quality further contribute to suspicion.
- High network risk due to localhost network calls
- Low maintainer activity and poor metadata quality
Per-check LLM notes
- Network: The presence of network calls to localhost suggests potential unexpected behavior or hidden functionality that may be used for data exfiltration or command and control.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating likely legitimate use.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, which could indicate a lack of transparency or intent to deceive.
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
f get_inn(self): r = requests.get("http://127.0.0.1:4444/TransferSimulator/inn") selfreturn r = requests.post( "http://127.0.0.1:8000/validate_inn",
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 PyQt5-sqlite3
Create a simple task management application using Python and the PyQt5-sqlite3 package. This app will allow users to manage their daily tasks by adding, editing, deleting, and marking tasks as completed. The application should have a clean and intuitive graphical user interface (GUI) that makes it easy for users to interact with their tasks. ### Key Features: - **Task Addition**: Users should be able to add new tasks with a title, description, and due date. - **Task Editing**: Tasks can be edited at any time to update their details. - **Task Deletion**: Users should have the ability to delete tasks they no longer need. - **Marking Tasks as Completed**: Each task should have a checkbox that allows users to mark them as completed. - **Search Functionality**: Implement a search bar where users can search for specific tasks by title or description. - **Sorting Options**: Allow sorting of tasks by due date or status (completed vs. not completed). ### Utilizing PyQt5-sqlite3: - Use PyQt5 for building the GUI components such as buttons, text boxes, and labels. - Leverage SQLite through PyQt5-sqlite3 to store and retrieve task data. Ensure data persistence so that tasks remain even after closing and reopening the application. - Implement CRUD (Create, Read, Update, Delete) operations on the SQLite database for managing tasks. ### Additional Considerations: - Design the UI with modern aesthetics and ensure it is responsive and user-friendly. - Include error handling to provide meaningful feedback when something goes wrong, like attempting to delete a non-existent task. - Provide clear instructions within the application on how to use each feature.