alfasim-sdk

v1.6.0 suspicious
4.0
Medium Risk

ALFAsim API/SDK

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential code injection due to the use of 'eval' with user-controlled input, raising concerns about its security. However, other aspects like network and shell risks are relatively low.

  • Use of 'eval' with potentially user-controlled input indicates high obfuscation risk.
  • No network calls or suspicious shell executions detected.
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Shell executions are likely for build and setup purposes, but no suspicious commands were observed.
  • Obfuscation: The use of 'eval' with a potentially user-controlled input is concerning and could indicate obfuscation or code injection risks.
  • Credentials: No direct evidence of credential harvesting patterns was found.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • 5 test file(s) detected (e.g. test_alfasim_sdk_utils.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1309 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 415 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 16 unique contributor(s) across 100 commits in esss/alfasim-sdk
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • ar: evaluated_value = eval(self.expr, BUILT_IN_VARS, namespace) if self.categor
  • at: evaluated_value = eval(self.expr, BUILT_IN_VARS, namespace) return evaluate
  • ): return eval(value, BUILT_IN_VARS, namespace) case unreac
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • xit(message=msg, code=1) subprocess.check_call([f"{cmake_cmd}"] + cmake_args) subprocess.check_call(
  • make_cmd}"] + cmake_args) subprocess.check_call( [ f"{cmake_cmd}", "--build"
  • d = shutil.which("cmake") subprocess.check_call([f"{cmake_cmd}"] + cmake_args) def _remove_hmplugin_files(
  • ss(str(cwd), os.W_OK) subprocess.run(command, cwd=str(cwd), env=current_env, check=True) @pytes
  • : Path) -> Path: result = subprocess.run( [ f"{alfasim_sdk_cmd}", "ne
  • ch.chdir(new_plugin_dir) subprocess.run( [f"{invoke_cmd}", "compile"], ) artifacts_d
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: esss.co

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository esss/alfasim-sdk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ESSS" 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 alfasim-sdk 
Create a simulation dashboard using the ALFAsim SDK (Python package 'alfasim-sdk'). This dashboard will allow users to input various parameters related to fluid dynamics simulations, such as flow rates, temperatures, and pressures, and visualize the results in real-time. The application should include the following features:

1. A user-friendly interface where users can enter their simulation parameters.
2. Integration with the ALFAsim SDK to perform the actual simulations based on the input parameters.
3. Real-time visualization of simulation results, including graphs and charts.
4. The ability to save and load previous simulation scenarios for easy re-running.
5. An option to export the simulation data into a CSV file for further analysis.
6. Error handling to ensure robustness and user feedback in case of incorrect inputs or other issues.

The ALFAsim SDK will be utilized primarily for setting up and running the simulations based on the user-defined parameters. Users will interact with the dashboard through a simple web interface built using Flask or a similar Python web framework. The frontend will use JavaScript libraries like Plotly.js for real-time data visualization. The backend will handle the communication between the frontend and the ALFAsim SDK, executing simulations and returning results for display. This project aims to provide a practical example of integrating complex scientific simulation tools into a user-friendly application.

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