asyncua

v2.0 safe
3.0
Low Risk

Pure Python OPC-UA client and server library

🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe based on the low risk scores across various categories, with no indications of malicious intent or activity.

  • Low network and shell risk
  • Some obfuscation through base64 encoding, but common practice
  • Incomplete metadata and potentially new/inactive author account
Per-check LLM notes
  • Network: No network call patterns detected, which is normal for many packages, especially those focused on local operations.
  • Shell: No shell execution patterns detected, indicating the package does not attempt to execute system commands.
  • Obfuscation: The use of base64 decoding may indicate an attempt to obfuscate code, but it is also common in legitimate applications for data encoding and decoding purposes.
  • Credentials: No clear signs of credential harvesting were detected.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some concerns. However, there are no typosquatting or other severe red flags.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8163 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 898 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 5 unique contributor(s) across 100 commits in FreeOpcUa/opcua-asyncio
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • de() mytext = base64.b64decode(mytext) obj.value = mytext elif ntag ==
  • field, without going through eval(). Used by make_structure when building dataclass field
✓ 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: gmail.com>

⚠ Suspicious Page Links score 6.0

Found 3 suspicious link(s) on the package page

  • Non-HTTPS external link: http://freeopcua.github.io/,
  • Non-HTTPS external link: http://opcua-asyncio.rtfd.io/
  • Non-HTTPS external link: http://freeopcua.github.io/
✓ Git Repository History

Repository FreeOpcUa/opcua-asyncio 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 asyncua 
Create a real-time monitoring tool using the 'asyncua' Python package. This tool will connect to an OPC-UA server and retrieve data from industrial sensors such as temperature gauges, pressure meters, and flow rate indicators. The application should allow users to visualize the sensor data in real-time on a graphical interface, with options to set up alerts based on thresholds defined for each sensor type. Additionally, implement functionality to log historical data into a local SQLite database for future analysis.

Step-by-step requirements:
1. Set up an environment with Python and install the 'asyncua' package.
2. Develop a connection manager that establishes a secure connection to the OPC-UA server.
3. Implement a discovery mechanism to find available nodes (sensors) and their attributes on the server.
4. Design a user-friendly GUI using a library like Tkinter or PyQt to display real-time sensor readings.
5. Integrate alerting mechanisms that notify users via email or SMS if any sensor value exceeds predefined thresholds.
6. Save sensor data into a local SQLite database for archival purposes.
7. Provide an option to export the logged data into CSV format for external analysis tools.
8. Ensure the application runs efficiently using asynchronous programming techniques provided by 'asyncua'.

Features:
- Real-time data visualization
- Customizable alert thresholds
- Data logging into SQLite database
- Historical data export
- Secure OPC-UA communication
- User-friendly graphical interface

Utilizing 'asyncua': The package will be central to establishing the connection with the OPC-UA server, subscribing to nodes for real-time data updates, handling security aspects of the communication, and managing asynchronous operations for efficient data retrieval and processing.

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