🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls detected and no signs of obfuscation or credential mishandling. The metadata risk is slightly elevated due to the author having only one package.

Low network risk
No shell execution detected
No obfuscation patterns found
Single package by author

Per-check LLM notes

Network: No network calls detected, which is unusual for a client package but may be due to conditional network usage or misconfiguration in the test environment.
Shell: No shell execution patterns detected, indicating no immediate risk from executing system commands.
Obfuscation: No obfuscation patterns detected, suggesting legitimate use without hidden code.
Credentials: No credential harvesting patterns detected, indicating safe handling of secrets.
Metadata: The author has only one package, which might indicate a new or less active account but no other suspicious activities were flagged.

🔬 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: affinidi.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository affinidi/affinidi-tdk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Affinidi" 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 affinidi_tdk_vault_data_manager_client

Your task is to develop a user-friendly desktop application using Python that allows users to securely manage their digital identities and credentials. This application will utilize the 'affinidi_tdk_vault_data_manager_client' package to interact with a vault system where sensitive information like personal data and credentials can be stored and managed. The application should have a simple graphical interface built with PyQt5 or Tkinter, allowing users to perform various operations related to their digital identities.

Key Features:
1. User Registration: Users should be able to register an account within the application. Upon registration, a unique vault will be created for them using the 'affinidi_tdk_vault_data_manager_client' package.
2. Data Storage: Users should be able to store different types of data such as personal identification documents, certificates, and other credentials in their vault. The application should use the package's capabilities to encrypt and securely store this data.
3. Data Retrieval: Implement functionality that allows users to retrieve any data they've stored in their vault. Ensure that access is secure and requires authentication.
4. Data Deletion: Provide an option for users to delete any data from their vault securely. Use the package's methods to ensure that deleted data cannot be recovered.
5. Backup and Restore: Enable users to back up their vault data to another location and restore it if needed. Utilize the package's backup and restore functionalities to achieve this.
6. Security Measures: Integrate robust security measures into the application to protect user data at all times. Use encryption provided by the package and implement two-factor authentication.
7. User Interface: Design an intuitive and easy-to-navigate GUI using PyQt5 or Tkinter that guides users through each operation seamlessly.

The application should demonstrate proficiency in using the 'affinidi_tdk_vault_data_manager_client' package to manage user data securely and efficiently. Additionally, include comprehensive documentation detailing how to install dependencies, run the application, and how each feature works internally.