🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has limited shell execution risks but shows some red flags such as an anonymous author and low activity in the git repository, which raises suspicion about its legitimacy and purpose.

Anonymous author
Low activity in the git repository

Per-check LLM notes

Network: No network calls detected, which is normal and expected.
Shell: Shell execution is limited to updating desktop database, likely benign but could indicate an attempt to integrate with the system's GUI.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows some red flags such as an anonymous author and low activity in the git repository, but no clear signs of typosquatting or malicious intent.

🔬 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)

esktop_path) try: subprocess.run( ["update-desktop-database", applications_dir],

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.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 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 academic-contacts

Create a comprehensive academic contact management system using the Python package 'academic-contacts'. This mini-app should allow users to organize their academic contacts efficiently, including professors, colleagues, and peers. Here’s a step-by-step guide on how to develop this application:

1. **Setup**: Begin by installing the 'academic-contacts' package and setting up your Python environment.
2. **User Interface**: Design a user-friendly interface where users can easily add, view, edit, and delete contact information. Consider integrating a search feature to quickly locate specific contacts.
3. **Contact Management**: Utilize the 'academic-contacts' package to manage contact details such as name, affiliation, department, email, and research interests. Ensure the application supports adding multiple affiliations or departments for each contact.
4. **Integration of Academic Data**: Enhance the app by allowing users to import academic data from various sources like CVs or academic profiles. Use 'academic-contacts' to parse and structure this data into a manageable format.
5. **Notifications and Reminders**: Implement a feature that reminds users about upcoming meetings or events related to their contacts. Users should be able to set custom reminders based on contact-related activities.
6. **Export Options**: Provide options for users to export their contact lists in different formats such as CSV or Excel, making it easy to share or back up their data.
7. **Security Measures**: Ensure that user data is stored securely and that only authorized users have access to contact information. Implement basic security measures like password protection.
8. **Testing and Feedback**: Conduct thorough testing to ensure all features work seamlessly. Gather feedback from users to improve the application further.

This project aims to create a robust tool that simplifies academic networking and collaboration.