🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate level of suspicion due to its metadata issues, including a lack of maintainer history and an absence of an associated GitHub repository. While direct security risks are minimal, these factors suggest potential concerns.

Lack of maintainer history
No associated GitHub repository

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: Shell execution might be legitimate if AceCG needs to run commands locally, but it should be documented and reviewed.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows several red flags including lack of maintainer history, no associated GitHub repo, and a missing author name, suggesting potential risks.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

t_path.name] result = subprocess.run(cmd, cwd=str(plan.run_dir)) return RunResult(

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 10.0

5 maintainer concern(s) found

Only one version has ever been released — brand new package
Package is very new: uploaded 2 day(s) ago
Author name is missing or very short
Author "" 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 AceCG

Develop a comprehensive molecular simulation tool using the AceCG package. This tool will enable users to perform coarse-graining on molecular systems, which simplifies complex molecular structures into fewer, larger particles for easier computational analysis. The project should include the following steps and features:

1. **Setup**: Begin by installing the AceCG package and setting up a virtual environment for your project.
2. **User Interface**: Design a simple, intuitive user interface where users can input their molecular system data (e.g., PDB files).
3. **Molecular Data Input**: Allow users to upload their molecular structure files. Ensure compatibility with common file formats like PDB and XYZ.
4. **Coarse-Graining Parameters Configuration**: Provide options for users to configure coarse-graining parameters such as force field type, mapping rules between atom types and coarse-grained beads, and interaction potentials.
5. **Simulation Execution**: Implement functionality to execute coarse-graining simulations based on user inputs and configurations. Use AceCG’s core features to handle the computational heavy lifting.
6. **Visualization**: Integrate visualization tools to display the results of the coarse-graining process. Users should be able to visualize both the original and coarse-grained molecular structures.
7. **Output and Export**: Enable users to export the results of their simulations in various formats (PDB, XYZ, etc.). Additionally, provide detailed reports summarizing the coarse-graining process and key findings.
8. **Documentation and Help**: Create comprehensive documentation and help guides to assist users in understanding how to use the tool effectively.

In utilizing AceCG, focus on leveraging its capabilities for handling complex molecular systems, configuring force fields, and simulating interactions under different conditions. Your goal is to create a user-friendly yet powerful tool that democratizes access to advanced molecular simulation techniques.