NEMO-sensors

v1.2.1 suspicious
4.0
Medium Risk

Plugin for NEMO providing support for connecting to Modbus sensors

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks associated with network, shell, and obfuscation activities, but the metadata suggests potential issues with the author's account being new or inactive.

  • Incomplete author information
  • New or inactive author account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some 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

Email domain looks legitimate: nist.gov>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository usnistgov/NEMO-sensors appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with NEMO-sensors 
Create a real-time monitoring system for industrial environments using the 'NEMO-sensors' package. This system will allow users to connect to multiple Modbus sensors, retrieve data such as temperature, pressure, and humidity, and visualize this data in a user-friendly interface. Additionally, the application should have the capability to log sensor readings into a local database for historical analysis.

Step-by-Step Instructions:
1. Set up a Python virtual environment and install the necessary packages including 'NEMO-sensors'.
2. Develop a configuration file where users can specify the details of their Modbus sensors, such as IP addresses, port numbers, and sensor types.
3. Implement a function that connects to each specified Modbus sensor and retrieves the current readings.
4. Create a graphical user interface (GUI) using a library like Tkinter or PyQt that displays the sensor data in real-time.
5. Integrate a logging feature that saves the sensor readings into a SQLite database at regular intervals.
6. Add an option within the GUI to view historical data from the database.
7. Ensure the application can handle exceptions and errors gracefully, providing clear feedback to the user if issues arise during communication with the sensors.
8. Test the application thoroughly under various conditions to ensure reliability and accuracy.

Suggested Features:
- Support for different types of Modbus sensors (e.g., temperature, pressure, humidity).
- Real-time graphing of sensor data using matplotlib or a similar plotting library.
- Ability to set thresholds for sensor values and trigger alerts when these thresholds are exceeded.
- Option to export historical data to CSV files for further analysis.
- User authentication and role-based access control for multi-user environments.