🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits signs of obfuscation and has metadata indicating low maintainer engagement, which raises concerns about its legitimacy and purpose.

High obfuscation risk
Low maintainer engagement indicated by metadata

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious activities.
Obfuscation: The code shows signs of obfuscation through commented-out sections and unusual patterns which may indicate an attempt to hide functionality.
Credentials: No clear evidence of credential harvesting is present in the provided code snippets.
Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate low effort or potential risk.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

# @classmethod # def eval(cls, *args): # if any([not isinstance(arg, Number) f
n): @classmethod def eval(cls, *args): if len(args) != 1: raise Va
, self.RHS, modules) def eval(self, *args: Union[np.ndarray]) -> np.ndarray: retur
""" @classmethod def eval(cls, *args): return None def _numpycode(self, p
""" @classmethod def eval(cls, *args): # Don't auto-simplify; keep the applica
""" @classmethod def eval(cls, n): # Don't auto-simplify; we want a Function a

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: foxmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository smallbunnies/Solverz 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 Solverz

Create a mini-application called 'CitySim' using the Python package 'Solverz', which is designed for simulation modeling. Your goal is to simulate the growth and development of a city over time, considering factors like population dynamics, infrastructure expansion, and economic activities. This application should allow users to input various parameters such as initial population size, land area, economic growth rate, and infrastructure development pace. Additionally, it should provide visual outputs showing how these factors evolve over a specified period.

Key Features:
1. User Input Interface: Allow users to set initial conditions for their city simulation, including population size, available land area, economic growth rate, and infrastructure development speed.
2. Simulation Engine: Utilize Solverz to model the interactions between population growth, land use changes, economic activities, and infrastructure developments. Ensure the simulation runs over a customizable timeframe.
3. Visualization Module: Implement a feature to visualize the simulation results, showing how the city evolves over time. Consider using graphs, charts, and maps to represent different aspects of the simulation.
4. Scenario Analysis: Enable users to run multiple scenarios based on different inputs or assumptions, allowing them to compare outcomes and understand the impact of varying factors.
5. Reporting Tool: Provide a reporting tool that summarizes key findings from each simulation run, highlighting trends and insights derived from the data.

How to Use Solverz:
- Define the model structure using Solverz' syntax, specifying equations that govern population growth, land use changes, economic activities, and infrastructure developments.
- Set up initial conditions and parameters for the simulation.
- Run the simulation using Solverz' solver functions, which will compute the evolution of the city over time based on the defined model and inputs.
- Extract simulation results and feed them into the visualization module for graphical representation.
- Use Solverz' capabilities for scenario analysis by modifying input parameters and running additional simulations.