🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to network and shell execution vulnerabilities, despite having low risks in credential handling and obfuscation. The metadata quality and maintainer activity levels raise additional concerns.

network risk due to token-based authorization and SMTP calls
shell risk from executing commands via Popen

Per-check LLM notes

Network: The presence of token-based authorization and SMTP calls suggests potential unauthorized network communications.
Shell: Executing commands via Popen can be risky if not properly sanitized, indicating possible execution of arbitrary code.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising concerns but not conclusive evidence of malintent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

) session = requests.session() session.headers.update({"Authorization": f"Token {nb_t
l}" # self.session = requests.session() # self.session.headers.update() # self.ses
et_content(message) with smtplib.SMTP("localhost") as s: s.send_message(msg) def normali

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

current_run = subprocess.Popen(cmd_args, stderr=subprocess.PIPE) logger.inf

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: umich.edu>

✓ 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 agador

Create a network monitoring tool called 'NetWatch' using the Python package 'agador'. This tool will help users monitor their network traffic in real-time, providing insights into various aspects of their internet usage such as bandwidth consumption, active connections, and packet analysis. Here’s a step-by-step guide on how to develop this tool:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the 'agador' package which you can install via pip.
2. **Core Functionality**: Use 'agador' to gather network data such as incoming and outgoing packets, IP addresses involved, and types of traffic (e.g., HTTP, HTTPS, FTP). Implement functions within NetWatch to parse and analyze this raw data.
3. **Real-Time Monitoring**: Develop a feature that displays this information in real-time through a user-friendly interface. Consider using libraries like Tkinter or PyQt for GUI development.
4. **Data Visualization**: Integrate visualization tools to represent collected data graphically. Libraries like Matplotlib or Plotly can be used to display trends over time, such as bandwidth usage per hour/day/week.
5. **Alert System**: Implement an alert system that notifies users when certain thresholds are exceeded (e.g., high bandwidth usage, suspicious activity).
6. **Export Data**: Allow users to export the gathered data into formats like CSV or Excel for further analysis.
7. **User Interface Enhancements**: Continuously refine the user interface based on feedback from beta testers. Focus on making it intuitive and easy to understand.
8. **Security Measures**: Since NetWatch deals with sensitive network data, ensure appropriate security measures are in place to protect user privacy.

By following these steps, you'll create a powerful yet accessible network monitoring tool that leverages the capabilities of 'agador' to provide deep insights into network behavior.