AI Analysis
The package appears safe based on the lack of indications of malicious activities such as shell execution, obfuscation, or credential harvesting. However, the metadata risk score is moderately high due to potential inactivity or lack of community involvement.
- No shell execution detected
- No signs of code obfuscation
- Repository shows low community engagement
Per-check LLM notes
- Network: The use of httpx.Client with a timeout suggests the package is making network requests, which could be legitimate if it's interacting with Aruba Central APIs.
- Shell: No shell execution patterns were detected, indicating no immediate risk from command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious intent related to stealing secrets.
- Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.
Package Quality Overall: Low (4.6/10)
Partial test coverage signals detected
2 test file(s) detected (e.g. test_client.py)
Some documentation present
Detailed PyPI description (5909 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
27 type-annotated function signatures detected in source
Limited contributor diversity
1 unique contributor(s) across 26 commits in shigechika/aruba-central-mcpSingle author but highly active (26 commits)
Heuristic Checks
Found 1 network call pattern(s)
t_secret self._http = httpx.Client(timeout=120) self._token: str | None = None
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
1 maintainer concern(s) found
Author "AIKAWA Shigechika" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to develop a small but impactful application using the Python package 'aruba-central-mcp'. This package serves as a bridge between the Aruba Central network management platform and AI assistants, providing access to real-time statuses of Access Points (APs), switches, and clients. Your application will be called 'NetworkGuard' and it will monitor and alert on critical network statuses. Hereβs how youβll build it step-by-step: 1. **Setup**: Begin by installing the 'aruba-central-mcp' package and setting up your environment. Ensure you have the necessary credentials and permissions from Aruba Central to access the network statuses. 2. **Data Retrieval**: Use the 'aruba-central-mcp' package to fetch real-time data about APs, switches, and clients. Implement functions to retrieve and parse this data efficiently. 3. **Monitoring Logic**: Develop monitoring rules within NetworkGuard. These rules should check for specific conditions such as high CPU usage on APs, low connectivity rates, or unusual client behavior. 4. **Alerting System**: When a rule condition is met, NetworkGuard should trigger alerts. Alerts can be via email, SMS, or through a notification service. Consider integrating multiple alert channels. 5. **User Interface**: Create a simple web interface where users can view current network statuses, set their own monitoring rules, and manage alerts. 6. **Logging & Reporting**: Include logging capabilities to track all activities and generate reports for historical analysis and troubleshooting. Suggested Features: - Customizable thresholds for alerting based on network conditions. - Historical data storage for trend analysis. - Integration with popular third-party alert services like PagerDuty or OpsGenie. - Role-based access control for different levels of user interaction with NetworkGuard. By leveraging the 'aruba-central-mcp' package, your application will provide a robust solution for network administrators to maintain optimal network performance and quickly respond to issues.
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