QuLab

v2.13.1 suspicious
5.0
Medium Risk

contral instruments and manage data

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential shell execution and significant obfuscation techniques, which could mask malicious activities. Further investigation is warranted.

  • Shell execution detected
  • Significant obfuscation through base64 decoding and eval usage
Per-check LLM notes
  • Network: No network calls detected, which is normal and not indicative of malicious activity.
  • Shell: Shell execution detected may be for legitimate purposes like running scripts, but requires further review to ensure it's not being exploited.
  • Obfuscation: The code shows signs of obfuscation through base64 decoding and the use of eval which can hide malicious intent.
  • Credentials: No clear evidence of credential harvesting, but the presence of an input request for a key value could be suspicious.
  • Metadata: The maintainer has an incomplete profile and a new account, which may indicate a lack of trustworthiness.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

  • ng_code): mapping_bytes = base64.b64decode(mappping_code) if hash_str != hashlib.md5(mapping_bytes)
  • g) try: value = eval(value) except: pass reg.set(key, value)
  • except: value = eval(input(f'"{self.key}": ')) return value def a
  • mespace = { "np": __import__("numpy"), "ctx": ctx, "__name__": "__skill__
  • self.result = pickle.loads(msg) except Exception as e:
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ified environment proc = subprocess.Popen([sys.executable, script_path, *args],
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository feihoo87/QuLab 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 QuLab 
Your task is to develop a mini-application named 'QuantumLabManager' using the Python package 'QuLab'. This application will serve as a comprehensive tool for researchers and engineers working in quantum physics and related fields. The goal of QuantumLabManager is to streamline the process of controlling laboratory instruments and managing experimental data. Here’s a detailed breakdown of what the application should accomplish:

1. **Instrument Control**: Implement functionality to connect to various laboratory instruments such as signal generators, oscilloscopes, and power supplies. Use 'QuLab' to control these instruments, allowing users to set parameters like frequency, amplitude, and voltage.
2. **Data Acquisition**: Integrate a feature that automatically collects data from connected instruments during experiments. Ensure that the data is stored efficiently using 'QuLab', with options to specify file formats and storage locations.
3. **Data Analysis**: Provide tools within the application for basic analysis of collected data, including plotting graphs and calculating statistical metrics. Utilize 'QuLab' to process and analyze the data, ensuring compatibility with the data acquisition module.
4. **Experiment Management**: Allow users to define, save, and run predefined experiment protocols. Each protocol should include steps for instrument setup, data collection, and analysis. Use 'QuLab' to manage these protocols seamlessly.
5. **User Interface**: Design a user-friendly graphical interface for easy interaction with all the above functionalities. The UI should be intuitive, allowing users to control instruments, view live data, and perform analyses without needing extensive technical knowledge.
6. **Documentation and Help**: Include comprehensive documentation and help resources within the application. Users should be able to access tutorials, FAQs, and example scripts directly from the app.

Utilize 'QuLab' throughout the development process to leverage its capabilities in instrument control and data management. Ensure that the application is robust, scalable, and can handle multiple concurrent experiments. Additionally, consider implementing error handling and logging mechanisms to improve reliability and ease of debugging.