AI Analysis
The package shows moderate risk due to potential shell execution risks and the maintainer's lack of a linked GitHub repository, indicating possible early-stage malicious intent or supply-chain attack.
- High shell risk due to Git command execution
- Maintainer lacks a linked GitHub repository
Per-check LLM notes
- Network: The network calls are likely for legitimate API interactions, but further investigation is needed to confirm the endpoints and data exchanged.
- Shell: The shell execution pattern suggests the package may execute Git commands, which could be risky if it's interacting with external repositories or executing arbitrary code.
- Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The maintainer has a new or inactive PyPI account and lacks a GitHub repository link, which may indicate potential risk.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (1854 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
38 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 4 network call pattern(s)
str, Any]: async with httpx.AsyncClient(base_url=self._base_url, timeout=_TIMEOUT) as c:= severity async with httpx.AsyncClient(base_url=self._base_url, timeout=_TIMEOUT) as c:ss, …).""" async with httpx.AsyncClient(base_url=self._base_url, timeout=_TIMEOUT) as c:""" async with httpx.AsyncClient(base_url=self._base_url, timeout=_TIMEOUT) as c:
No obfuscation patterns detected
Found 1 shell execution pattern(s)
e.""" try: proc = subprocess.run( ["git", *args], cwd=cwd,
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
1 maintainer concern(s) found
Author "ArrowShield" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully-functional mini-application called 'MCP Monitor' that leverages the ArrowShield MCP server package to monitor and manage multiple ArrowShield MCP servers efficiently. This application will serve as a centralized dashboard where users can control, monitor, and troubleshoot their ArrowShield MCP servers from a single interface. ### Core Features: 1. **Server Management**: Allow users to add, remove, and configure ArrowShield MCP servers within the application. Users should be able to specify server details such as IP address, port, and authentication credentials. 2. **Real-Time Monitoring**: Implement real-time monitoring of server status, including CPU usage, memory usage, and network activity. Display these metrics in a user-friendly graphical format, such as charts or gauges. 3. **Alert System**: Set up an alert system that notifies users via email or SMS when certain thresholds are exceeded, such as high CPU usage or low memory availability. 4. **Log Analysis**: Integrate a log analysis feature that parses and displays logs from each server in a structured format. Users should be able to filter logs based on time, severity, and keywords. 5. **Remote Commands**: Enable users to send remote commands to servers directly from the application interface. These commands could include restarting services, updating configurations, or running diagnostics. 6. **User Interface**: Design a clean, intuitive user interface that allows easy navigation between different features and settings. Use modern web technologies like React or Vue.js for the front-end. ### Utilizing ArrowShield MCP Package: - Use the `arrowshield-mcp` package to establish secure connections with each ArrowShield MCP server. - Leverage the package’s APIs to retrieve server statistics, manage configurations, and execute commands remotely. - Implement error handling and logging mechanisms provided by the package to ensure robustness and reliability of the application. ### Development Steps: 1. **Setup Project Environment**: Initialize a new Python project and install necessary dependencies, including the `arrowshield-mcp` package. 2. **Design Database Schema**: Plan out the database schema to store server information, user settings, and logs. 3. **Develop Backend Logic**: Write backend logic using Python and Flask/Django to handle server communication, data retrieval, and command execution. 4. **Build Frontend Interface**: Create the frontend interface using React/Vue.js to interact with the backend API and display real-time data. 5. **Implement Alert System**: Develop an alert system that sends notifications based on predefined conditions. 6. **Test and Debug**: Thoroughly test the application for bugs and performance issues, fixing them before deployment. 7. **Deploy Application**: Deploy the application on a cloud platform like AWS or Heroku, ensuring it is scalable and secure.
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