AI Analysis
Final verdict: SUSPICIOUS
The package shows potential for misuse due to its network interactions and the lack of maintainer history, although no direct malicious activities have been confirmed.
- Network risk due to token-based authentication and session management
- Low maintainer activity and history
Per-check LLM notes
- Network: The use of requests.Session() suggests network interaction which is common for client packages like asiacellclient, but the context of 'gent()' and handling tokens needs further investigation to ensure proper usage.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package is new and the maintainer has limited history, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (2.8/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (2702 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
4 type-annotated function signatures (partial)
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
gent() self.session = requests.Session() if token: self.set_token(token)
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: darksidehost.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "KingZero" 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 asiacellclient
Create a Python-based mobile data usage tracker application that leverages the unofficial AsiaCell Python SDK ('asiacellclient') to provide users with real-time insights into their mobile data consumption. This application will allow users to authenticate via SMS, retrieve their current data balance, and monitor their monthly data usage trends. Additionally, the app should alert users when they are approaching their monthly data limit. Here’s a detailed breakdown of the steps and features you need to implement:
1. **User Authentication**: Develop a simple user interface where users can input their phone number and receive an authentication code via SMS from AsiaCell. Use the 'asiacellclient' package to initiate the authentication process.
2. **Data Balance Retrieval**: Once authenticated, the application should use 'asiacellclient' to fetch the user's current data balance and display it in a user-friendly format.
3. **Monthly Data Usage Tracker**: Implement a feature that tracks the user's monthly data usage over time. Store the data locally or in a cloud database for future reference.
4. **Usage Alerts**: Set up notifications or alerts within the application to inform users when they are nearing their monthly data limit based on the information retrieved using 'asiacellclient'.
5. **Graphical Representation**: Provide visual representations of the user's data usage trends over time through graphs or charts.
6. **User Interface**: Design a clean, intuitive UI using Python’s Tkinter or another suitable GUI library.
7. **Documentation**: Ensure all functions and methods within your application are well-documented, including instructions on how to install and run the application.
This project aims to demonstrate proficiency in integrating third-party APIs, handling user authentication securely, and providing valuable insights through data visualization.
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