aionetiface

v0.0.24 suspicious
6.0
Medium Risk

Async Python networking with a unified Pipe API — TCP/UDP, IPv4/IPv6, multi-NIC, NIC enumeration, STUN, NAT classification — Windows XP → 11, Linux, macOS, BSD.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package aionetiface v0.0.24 is deemed suspicious due to the high risk of obfuscation through the use of eval() for string formatting, which can enable code injection. While there are no indications of credential harvesting or severe metadata risks, the presence of such risky practices raises concerns about potential malicious intent.

  • High obfuscation risk due to eval() usage
  • No signs of credential theft
Per-check LLM notes
  • Obfuscation: The use of eval() for string formatting is highly suspicious and can be used for code injection, indicating potential malicious obfuscation.
  • Credentials: No clear patterns indicative of credential harvesting were detected.
  • Metadata: The author has only one package, which may indicate a new or less active account, but no other red flags are present.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

  • Test runner config found: pyproject.toml
  • 1 test file(s) detected (e.g. test_init.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (9295 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in robertsdotpm/aionetiface
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • cy string formatter that uses eval() to expand {expr} placeholders. DEPRECATED — do not us
  • note: clean_and_eval() calls eval() against the caller's local and global namespaces. Nev
  • "fstr2 is deprecated and uses eval() — use f-strings or fstr() instead.", Deprecati
  • try: result = str(eval(replaced)) return result except (TypeErr
  • result = str(eval(replaced, self.f_locals, self.f_globals)) re
  • try: code_obj = compile(wrapper, filename, "exec") except SyntaxError: self.showsyntaxer
⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

  • None try: proc = subprocess.Popen( list(argv), stdin=stdin_pipe,
  • None proc = subprocess.run( value, stdout=subpr
  • ion().major >= 6: subprocess.call( [ "netsh", "advfirewall
  • ) else: subprocess.call( [ "netsh", "firewall",
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: roberts.pm

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository robertsdotpm/aionetiface appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Matthew Roberts" 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 aionetiface 
Create a cross-platform network diagnostic tool using the 'aionetiface' Python package. This tool will allow users to perform various network-related tasks such as network interface enumeration, STUN requests, and NAT type detection. Here’s a detailed breakdown of the project steps and features:

1. **Project Setup**: Start by setting up your development environment with Python and installing the 'aionetiface' package.
2. **Network Interface Enumeration**: Utilize 'aionetiface' to list all available network interfaces on the user's machine, including their names, IP addresses, and other relevant information.
3. **STUN Request Functionality**: Implement a feature where the tool sends a STUN request to a public server to discover the external IP address of the user's device. Use 'aionetiface' to handle the asynchronous communication necessary for this task.
4. **NAT Type Detection**: Extend the tool to classify the type of NAT (e.g., Full Cone, Restricted Cone, Port Restricted Cone, Symmetric) that the user's network is behind. This involves sending specific packets and analyzing the responses, which can be facilitated through 'aionetiface'.
5. **User Interface**: Design a simple command-line interface (CLI) for the tool, allowing users to select between different functionalities like enumerating interfaces, performing STUN requests, or checking their NAT type.
6. **Error Handling & Logging**: Ensure robust error handling and logging mechanisms are in place to capture any issues during execution, such as connectivity problems or incorrect input from the user.
7. **Testing**: Write tests to verify each feature works as expected across multiple platforms supported by 'aionetiface', including Windows, Linux, and macOS.
8. **Documentation**: Provide comprehensive documentation explaining how to install the tool, use its features, and understand the output.

By leveraging 'aionetiface', you'll be able to efficiently manage asynchronous networking tasks, making your network diagnostic tool both powerful and versatile.

💬 Discussion Feed

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