🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a high level of code obfuscation, which is concerning as it may hide malicious activities. Additionally, there are indications of low maintainer engagement and poor metadata quality, raising further suspicion.

High obfuscation risk
Poor metadata quality

Per-check LLM notes

Network: No network calls suggest normal behavior unless the package is purely local.
Shell: No shell executions indicate no immediate signs of malicious activity.
Obfuscation: The obfuscation pattern is suspicious and may indicate an attempt to hide code logic, but without additional context it's hard to determine if it's malicious.
Credentials: No clear signs of credential harvesting detected, however, the package should still be reviewed for any unusual access patterns.
Metadata: The package shows signs of low maintainer engagement and poor metadata quality, raising concerns but not definitive proof of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

ey = f"x['{key}']" node = eval(eval_key, {"x": Config._settings}) if key else Config._setti

✓ 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: 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 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 ab-engine

Create a fully functional mini-application that helps users manage their daily tasks and projects using the 'ab-engine' Python package. This application will serve as a personal task manager, enabling users to create, update, delete, and categorize tasks. Additionally, it will allow users to track the progress of their tasks and set reminders for upcoming deadlines. Here are the key steps and features for building this application:

1. **Setup**: Begin by installing the 'ab-engine' package along with any necessary dependencies. Ensure that your development environment is set up properly.
2. **Task Creation**: Implement functionality that allows users to add new tasks to their task list. Each task should include details such as title, description, due date, and category.
3. **Task Management**: Provide options for users to update or delete existing tasks. Also, implement sorting and filtering capabilities based on different attributes like due date or category.
4. **Progress Tracking**: Integrate a feature where users can mark tasks as completed or in progress. This will help them track their productivity over time.
5. **Reminders**: Set up a system that sends reminders to users about upcoming deadlines. This could be implemented through notifications or emails.
6. **User Interface**: Design a simple yet intuitive user interface that makes it easy for users to interact with the application. Consider both command-line and graphical interfaces.
7. **Data Persistence**: Use 'ab-engine' to store task data persistently so that it remains accessible across sessions.
8. **Testing and Validation**: Rigorously test all functionalities to ensure they work as expected. Validate user inputs to prevent errors and improve user experience.

In this project, the 'ab-engine' package will be crucial for handling data storage and retrieval operations. It will provide the backbone for managing task information efficiently and reliably.