🤖 AI Analysis

Final verdict: SUSPICIOUS

The package Azmir v0.1 exhibits low risks in terms of network, shell, and obfuscation activities, but its metadata suggests it may be newly created with little effort, raising suspicion about its authenticity and purpose.

Low metadata activity
Minimal package description

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access to function.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious activity.
Obfuscation: No obfuscation patterns detected, suggesting low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of being newly created with minimal activity and metadata, which could indicate low effort or potential malicious intent.

🔬 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Azmir Sharif" 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 Azmir

Create a fully-functional mini-application named 'TaskMaster' that leverages the 'Azmir' personal assistant package to manage daily tasks and reminders for users. TaskMaster should provide a user-friendly interface for adding, editing, and deleting tasks as well as setting up recurring reminders. Additionally, it should support integration with a calendar API like Google Calendar to sync tasks and reminders automatically.

Step-by-Step Guide:
1. Set up the basic structure of the application using Python's Flask framework for the backend and React.js for the frontend.
2. Integrate the 'Azmir' package to handle natural language processing for task creation and management commands such as 'Add a task', 'Edit my task for tomorrow', etc.
3. Implement a database (using SQLite for simplicity) to store user tasks and reminders.
4. Develop a RESTful API using Flask to communicate between the frontend and backend.
5. Create a simple yet intuitive UI with React.js where users can interact with their tasks and reminders.
6. Add functionality to set up recurring tasks and reminders using cron jobs or a similar scheduling mechanism.
7. Implement integration with Google Calendar API for syncing tasks and reminders.
8. Test the application thoroughly to ensure all functionalities work as expected.
9. Deploy the application on a cloud service provider like Heroku or AWS.

Suggested Features:
- Voice command support for adding and managing tasks (utilizing Azmir's NLP capabilities).
- Priority levels for tasks (High, Medium, Low).
- Due date and time for each task.
- Notifications for upcoming tasks and reminders.
- User authentication and authorization for secure access.
- Export tasks and reminders to CSV files.

How 'Azmir' Package is Utilized:
- For handling natural language inputs from users for task creation, editing, and deletion.
- To understand and process voice commands for task management.
- For generating and sending notifications based on user preferences and task deadlines.