Ripple-hpc

v1.4.2 safe
3.0
Low Risk

High-performance molecular dynamics trajectory analysis (RDF, SSF, VHF, ISF, four-point functions, diffusion and non-Gaussian metrics).

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with obfuscation and credential harvesting. However, there are concerns about its maintenance level and potential changes in authorship.

  • Low obfuscation risk
  • Low credential risk
  • Potential new authorship and low maintenance
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintenance and potentially new authorship, raising some suspicion but not conclusive evidence of 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

No author email provided

Suspicious Page Links

All external links appear legitimate

Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Frost research group" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with Ripple-hpc
Develop a Python-based molecular dynamics analysis tool using the 'Ripple-hpc' package. This tool will enable users to analyze molecular trajectories from simulations, focusing on key properties such as radial distribution function (RDF), static structure factor (SSF), van Hove correlation function (VHF), intermediate scattering function (ISF), and diffusion coefficients. The application should allow users to upload their simulation data, select which analysis methods they wish to apply, and then generate visual outputs of the results. Additionally, include an option for users to export their analysis data and graphs in common formats like CSV and PNG. Ensure that the user interface is intuitive, allowing both novice and experienced users to navigate easily. Use 'Ripple-hpc' to perform the heavy lifting of the computations, ensuring that the tool is efficient and capable of handling large datasets typical in molecular dynamics simulations.