Nuitka

v4.1.2 suspicious
5.0
Medium Risk

Python compiler with full language support and CPython compatibility

🤖 AI Analysis

Final verdict: SUSPICIOUS

Nuitka v4.1.2 exhibits a moderate risk level due to potential code obfuscation techniques that could mask malicious behavior. However, the lack of network calls and shell risks below critical thresholds suggest that the package's primary function is not overtly harmful.

  • High obfuscation risk due to use of eval and compile functions
  • Low network and credential risks
Per-check LLM notes
  • Network: No network calls detected, which is normal and expected.
  • Shell: Shell execution appears to be related to the package's functionality, but further review may be needed to ensure it does not pose a risk.
  • Obfuscation: The use of eval and compile functions with optimization settings suggests an attempt to obfuscate code execution, which could be indicative of malicious intent.
  • Credentials: No clear patterns of credential harvesting were detected.
  • Metadata: The maintainer has only one package, which might indicate a new or less active account, but there are no other suspicious flags.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • try: value = eval("{1,1.0}.pop()") # pylint: disable=eval-used except
  • is bytes: bytecode = compile( tree, filename=filename, mode="exec", dont_inherit=True, ) else:
  • imize = 1 bytecode = compile( tree, filename=filename, mode="exec", dont_inherit=True, optimize=optimize ) retur
  • python_command_template += ";__import__('%(module_name)s')" python_command = python_command_template % {
  • bytes: return str(__import__("TkInter").TkVersion) else: return str(__import__(
  • else: return str(__import__("tkinter").TkVersion) except ImportError: # This should le
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • os.name == "nt": os.system("") _enabled_ansi = True def hasTerminalLinkSuppo
  • ecoding error" process = subprocess.Popen( args=(sys.executable, source_filename), std
  • xecutable = None subprocess.check_call( command, executable=executa
  • mport subprocess exit_code = subprocess.call( %(scons_command)r, env={%(env)s}, shell=False )
  • try: result = subprocess.call(scons_command, shell=False, cwd=source_dir) exce
  • compilerProcess = subprocess.Popen( realCmdline, stdout=stdoutFile, stderr=stde
✓ 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 Nuitka/Nuitka appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Kay Hayen" 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 Nuitka 
Your task is to create a simple but useful utility called 'FileAnalyzer' using Python and the Nuitka package. This utility will help users analyze various aspects of files on their system, such as file size, modification date, and file type. Additionally, it will compile these functionalities into standalone executables for Windows, macOS, and Linux, showcasing Nuitka's cross-platform capabilities.

Step 1: Define the core functionalities of 'FileAnalyzer'. It should be able to:
- Accept a directory path from the user.
- List all files within the specified directory.
- Display each file's name, size, last modified date, and file type.
- Optionally, allow users to specify a file extension to filter results by.

Step 2: Implement these functionalities using Python. Ensure your code is modular and well-commented for clarity.

Step 3: Utilize the Nuitka package to compile the Python script into standalone executables. Follow Nuitka's documentation to ensure compatibility across different operating systems.

Suggested Features:
- Include a graphical user interface (GUI) using a library like Tkinter for better user interaction.
- Add functionality to compare two directories side by side for differences in files.
- Integrate a feature to sort files based on their attributes (size, date, etc.).
- Allow users to export the analysis results into a CSV file for further processing.

By completing this project, you'll not only have a practical tool at hand but also gain experience with Python's powerful libraries and the benefits of compiling Python applications with Nuitka.