🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity such as network calls or shell execution, however, the new and potentially inactive maintainer, coupled with low community engagement, raise concerns about its legitimacy and maintenance.

New and possibly inactive maintainer
Low community engagement

Per-check LLM notes

Network: No network calls detected, which is normal for most packages not requiring internet access.
Shell: No shell execution detected, indicating the package does not attempt to execute system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer seems new or inactive, and the repository lacks community engagement, which raises some suspicion but not enough to conclude malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ 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: 163.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "LiuGaoyong" 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 adsorption

Develop a mini-application called 'AdsorptionAnalyzer' that leverages the 'adsorption' package to simulate and analyze adsorption processes on surfaces using atomic simulations. This application will be designed to help materials scientists and researchers understand how gases interact with solid surfaces at the molecular level. The app should have a user-friendly interface where users can input parameters such as gas type, surface material, temperature, and pressure. Additionally, it should provide visualizations of the adsorption process and output key metrics like adsorption capacity and isotherms.

Key Features:
1. User Input Interface: Allow users to specify the gas type (from a predefined list), surface material, temperature range, and pressure range.
2. Simulation Engine: Utilize the 'adsorption' package to run simulations based on the provided inputs. Ensure the engine supports different types of adsorption models.
3. Visualization Module: Implement plots for isotherms and surface coverage over time. Use matplotlib or a similar library for plotting.
4. Output Metrics: Display key metrics such as maximum adsorption capacity, specific adsorption rates, and any anomalies detected during the simulation.
5. Report Generation: Provide an option to generate a PDF report summarizing the simulation results, including all visualizations and metrics.
6. Documentation: Include comprehensive documentation detailing how to use the application, interpret the results, and customize the simulations.

The 'adsorption' package will be crucial for running the core simulations and calculations required to model the adsorption process accurately. Users should be able to explore various scenarios and gain insights into the behavior of different gases on various surfaces under different conditions.