🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of network calls, shell execution, obfuscation, or credential harvesting, indicating a low risk profile.

No network calls detected
No shell execution detected

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external communication.
Shell: No shell execution detected, indicating the package does not attempt to execute system commands without user interaction.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate threat of secret or credential theft.

🔬 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: wustl.edu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

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 SOURSOP

Create a mini-application named 'DisorderPredictor' using Python that leverages the SOURSOP package to analyze and predict regions of disorder in protein sequences. The application should have a user-friendly command-line interface where users can input a protein sequence or upload a FASTA file containing multiple sequences. The app should then process these sequences using SOURSOP's simulation analysis capabilities to identify disordered regions within each sequence. Additionally, include features such as:

1. A summary report that highlights key disordered regions, their length, and potential implications on protein function.
2. Visualization of the protein sequence with colored markers indicating predicted disordered regions.
3. Option to save the output as a text file or image for further analysis or presentation.
4. Integration of additional bioinformatics tools (e.g., BLAST for sequence similarity searches) to enhance the application's functionality.

The core functionalities of SOURSOP should be utilized throughout the project to ensure accurate and reliable predictions of protein disorder. Make sure to document your code thoroughly and provide clear instructions for installing and running the application.