🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network usage, shell execution, obfuscation, and credential handling. However, the metadata risk score indicates potential issues with maintainer effort and lack of a public repository, warranting further investigation.

Low maintainer effort
Lack of public repository

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
Metadata: The package shows signs of low maintainer effort and lacks a public repository, raising some suspicion but not conclusive evidence of malice.

🔬 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

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 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 FtFastUI

Create a weather dashboard application using the Python package 'FtFastUI'. This application should allow users to input a city name and receive current weather conditions including temperature, humidity, wind speed, and a brief description of the weather (e.g., sunny, rainy). Additionally, the app should display a simple graphical representation of the temperature trends over the past week.

Step 1: Set up your development environment with Python and install the required packages, including 'FtFastUI' and any necessary weather API client (such as OpenWeatherMap).

Step 2: Design the user interface using 'FtFastUI' components. Ensure the design is intuitive and user-friendly, featuring a search bar for entering city names and a display area for showing weather details.

Step 3: Implement functionality to fetch weather data from the chosen API when a city is entered into the search bar. Display this information on the screen using 'FtFastUI' components such as labels, charts, and icons.

Step 4: Add a chart component to show the temperature trends over the past week. Use 'FtFastUI' to create a visually appealing line graph or bar chart that updates dynamically based on the selected city's historical weather data.

Step 5: Enhance the user experience by adding animations and transitions between different states of the application (e.g., loading state while fetching data).

Step 6: Test the application thoroughly to ensure it works correctly across different cities and handles errors gracefully (e.g., invalid city names).

The goal is to demonstrate the versatility and ease-of-use of 'FtFastUI' in building interactive web applications quickly and efficiently.