🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no direct evidence of malicious activity. However, the shell risk score suggests that further investigation into the legitimacy of shell executions is necessary.

Shell risk at 5/10 requires closer inspection of executed commands.
Maintainer has only one PyPI package, indicating potential new or less active account.

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: Shell execution patterns may indicate legitimate functionality but could also be used for malicious purposes; further investigation into the commands executed is recommended.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package on PyPI, which may indicate a new or less active account.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

se" ] subprocess.run(command, check=True) except ModuleNotFoundError:
oin(cmd)}\n\n" proc = subprocess.Popen( cmd, stdout=subprocess.PIPE, stderr=subprocess.

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: alumni.tsukuba.ac.jp

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository kinari-labwork/AltEx-BE appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Kinari Matsumoto" 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 AltEx-BE

Develop a web-based mini-application that leverages the 'AltEx-BE' Python package to assist biologists and geneticists in designing sgRNA sequences for exon skipping using base editors. The application should be user-friendly and allow users to input their gene of interest along with specific exons they wish to target for skipping. Here’s a step-by-step guide on how to build this application:

1. **Project Setup**: Start by setting up a virtual environment for your Python project and install necessary dependencies including Flask for the backend and Bootstrap for the frontend to ensure a responsive UI.
2. **Backend Development**:
- Integrate the 'AltEx-BE' package into your Flask app to handle the sgRNA design process based on user inputs.
- Create API endpoints for receiving gene and exon information from the frontend and returning designed sgRNA sequences.
3. **Frontend Development**:
- Design a clean and intuitive interface where users can input gene names and select exons for skipping.
- Implement form validation to ensure proper input format.
4. **Integration**:
- Connect the frontend forms to the backend API endpoints to enable real-time processing of sgRNA designs.
5. **Testing**:
- Thoroughly test both the frontend and backend functionalities to ensure accuracy and reliability of sgRNA designs.
6. **Deployment**:
- Deploy the application on a cloud platform like Heroku or AWS ensuring it remains accessible to users.

**Suggested Features**:
- User authentication to track saved designs and user preferences.
- A database to store user submissions and sgRNA results for future reference.
- An educational section explaining the importance of exon skipping and base editing.
- Integration with BLAST for quick sequence analysis.
- Real-time error checking and suggestions for better exon targeting.

This project aims to streamline the process of sgRNA design for researchers working with base editors, making it faster and more efficient to explore genetic modifications.