🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all checked areas with no network calls, shell executions, or obfuscations. The metadata quality is low, but this alone does not indicate malicious activity.

Low metadata quality
No detected malicious activities

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
Metadata: The package shows low effort in metadata and maintainer history, but there's no clear indication of malicious intent.

🔬 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 advoco

Create a Python-based mini-application named 'AdventSolver' using the 'advoco' package which is designed to assist in solving puzzles from the Advent of Code event. Your application should include the following functionalities:

1. User Authentication: Allow users to log in with their Advent of Code username and session token to fetch and solve daily puzzles.
2. Puzzle Fetching: Automatically download the puzzle description and input data for each day from the Advent of Code website.
3. Solution Submission: Provide a feature to submit solutions for each puzzle directly through the application, displaying whether the solution was correct or not.
4. Puzzle Solving Assistance: Implement a mode where the user can manually input their code to solve the puzzle, and the application will run it and display the results.
5. Daily Progress Tracking: Keep track of the user's progress throughout the Advent of Code event, including solved puzzles, attempts made, and time spent on each puzzle.
6. Hint System: Offer hints or clues for particularly challenging puzzles, enhancing the learning experience without giving away the solution.
7. Leaderboard Integration: Display a local leaderboard showing the fastest solvers for each puzzle among registered users.
8. Data Visualization: Include basic data visualization tools to show trends in solving times and success rates over the course of the event.

To utilize the 'advoco' package effectively, ensure you leverage its functions for parsing Advent of Code data, handling user authentication, and managing sessions. Additionally, explore integrating more advanced features of 'advoco' such as puzzle-specific utilities and error-handling mechanisms to make your application robust and user-friendly.