AI Analysis
Final verdict: SUSPICIOUS
The package has some concerns regarding its metadata and maintenance efforts, which raise suspicion about its legitimacy and security posture.
- Metadata risk noted due to low maintenance and effort
- No clear malicious activities detected but concerns over package hygiene
Per-check LLM notes
- Network: The network call pattern suggests legitimate HTTP requests, possibly for API interaction or web service communication.
- Shell: No shell execution patterns detected, indicating low risk for direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low maintenance and effort, but there's no direct evidence of malicious intent.
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 (13099 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
38 type-annotated function signatures detected in source
○ 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)
self.client = client or httpx.AsyncClient( headers=headers, timeout=10
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 axi-easyagent
Create a simple AI-driven task management system using the 'axi-easyagent' package. This system will allow users to add tasks, mark them as completed, and receive reminders based on their due dates. The application should also include a feature to categorize tasks into different projects or categories. Step 1: Set up your development environment with Python installed and create a virtual environment. Step 2: Install the 'axi-easyagent' package and any other necessary dependencies. Step 3: Define the structure of your tasks, including attributes like title, description, due date, status, and category. Step 4: Implement the functionality to add new tasks through a user-friendly interface (CLI or basic web interface). Step 5: Add a feature to mark tasks as completed and update their status accordingly. Step 6: Use 'axi-easyagent' to implement a reminder system that sends notifications when tasks are approaching their due dates. Step 7: Allow users to categorize tasks into different projects or categories for better organization. Step 8: Optionally, implement a search function to find tasks based on keywords or filters. Suggested Features: - User authentication and authorization (for a multi-user environment) - Integration with calendar apps for automatic task scheduling - Statistics and analytics about task completion rates - Support for recurring tasks Utilization of 'axi-easyagent': - Leverage 'axi-easyagent' to manage the state and behavior of your AI-driven task management system. - Use 'axi-easyagent' to handle the logic behind task reminders and notifications efficiently. - Explore advanced features of 'axi-easyagent' to enhance the AI capabilities of your system, such as natural language processing for task creation or categorization.
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