🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits multiple high-risk indicators including potential execution of shell commands and code obfuscation, suggesting it might have hidden functionalities. While it handles credentials securely, the combination of these risks raises concerns about its integrity.

High shell risk due to execution of shell commands
Significant obfuscation risk hiding true functionality

Per-check LLM notes

Network: Network requests appear to be used for checking external resources, possibly updates or dependencies.
Shell: Execution of shell commands suggests the package may perform system checks or install additional packages, which could be risky if not properly controlled.
Obfuscation: The code shows signs of intentional obfuscation to hide the underlying logic, which could be used to evade analysis or detection.
Credentials: The script prompts for a MongoDB password using getpass, which is a legitimate way to handle sensitive information but can also indicate an attempt to harvest credentials if not properly secured.
Metadata: The maintainer has a single package and the email domain is very short, but no other suspicious activities were detected.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

ec = missing[0] request = urllib.request.Request( spec.url, headers={ "Us
, ) try: with urllib.request.urlopen(request, timeout=timeout) as response: r
return target request = urllib.request.Request(spec.url, headers={"User-Agent": "InterOptimus/check
= None try: with urllib.request.urlopen(request, timeout=timeout) as response: t

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

return Structure.from_dict(__import__("json").loads(obj)) except Exception: return No
"" if importable: __import__(importable) out["mlip_module"] = importable out["ok"] = Tru
"" if importable: __import__(importable) out["mlip_module"] = importable s = Structure(

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

if shell: proc = subprocess.run( cmd[0] if len(cmd) == 1 and isinstance(cmd[
else: proc = subprocess.run( cmd, capture_output=True,
""" try: r = subprocess.run( ["ss", "-tln", "-H"], capture_outpu
装以进行 MongoDB 连通性检测…") subprocess.run( [sys.executable, "-m", "pip", "install", "pymon
+", " ".join(cmd)) return subprocess.run(cmd, check=True, text=True, **kwargs) def _pip_install(*,
return False r = subprocess.run( [conda, "env", "list"], capture_output=True

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

one: mongo_password = getpass.getpass(f"MongoDB password for {args.mongo_user}: ") mongo = {

✓ Typosquatting

No typosquatting candidates detected

⚠ Registered Email Domain score 3.0

Suspicious email domain flags: Very short email domain: sz.tsinghua.edu.cn

Very short email domain: sz.tsinghua.edu.cn

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository HouGroup/InterOptimus appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Yaoshu Xie" 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 InterOptimus

Create a mini-application called 'InterfaceSimulator' using the Python package 'InterOptimus'. This application will allow users to simulate high-throughput crystalline interface behaviors under various conditions. Users should be able to input parameters such as temperature, pressure, and material properties, and the app will output simulations of how these interfaces behave over time.

The application should include the following features:
1. User-friendly GUI built with Tkinter or PyQt, allowing users to easily input parameters and visualize results.
2. Capability to save simulation results as CSV files for further analysis.
3. Real-time visualization of interface behavior during simulations using matplotlib or similar plotting libraries.
4. Option to load pre-defined scenarios from JSON files for quick testing and demonstration purposes.
5. Detailed documentation and comments within the codebase to ensure maintainability and readability.

To utilize 'InterOptimus', integrate its core functionalities to handle the simulation logic. Specifically, use its high-throughput capabilities to run multiple simulations simultaneously, optimizing performance. Ensure that the application leverages 'InterOptimus' to provide accurate and efficient simulation outputs based on user inputs.