🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is marked as deprecated and redirects users to a new package, showing no direct malicious activities. However, the low maintainer activity and poor metadata quality raise some concerns about its legitimacy and ongoing support.

Deprecated package that redirects to a new package
Low maintainer activity and poor metadata quality

Per-check LLM notes

Network: No network calls detected, which is not necessarily suspicious but should be consistent with the package's intended functionality.
Shell: No shell execution patterns detected, indicating no immediate risk from command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising suspicion but not conclusive evidence of malice.

🔬 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

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 short
Author "" 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 agent-discover-scanner

Create a network monitoring tool using Python that leverages the 'agent-discover-scanner' package (now known as 'agentdiscover') to automatically discover and monitor active devices on a local network. Your tool should perform the following tasks:

1. Scan the local network for all active IP addresses.
2. Identify the type of device connected at each IP address (e.g., router, printer, computer).
3. Collect basic information about each device, such as operating system version and open ports.
4. Store this information in a database for historical tracking.
5. Provide a simple web interface to display the current status of all devices on the network.
6. Send alerts via email if any device goes offline unexpectedly.

To achieve these goals, you will need to utilize the 'agentdiscover' package to scan the network and gather initial data about the devices. The package can help in identifying active devices and potentially provide details about their services and types. Additionally, you'll need to integrate other Python libraries for database management (such as SQLite or PostgreSQL), web development (Flask or Django), and email sending (smtplib).

This project aims to give users a comprehensive view of their network environment, making it easier to manage and secure their devices.