🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk for network activity, shell execution, obfuscation, and credential harvesting. However, the missing maintainer's author name and the single package associated with the maintainer raise concerns about potential malicious intent.

Missing maintainer's author name
Single package associated with maintainer

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access to function properly.
Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer's author name is missing and they appear to have only one package, which could indicate a less established or potentially suspicious account.

📦 Package Quality Overall: Low (4.6/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

8 test file(s) detected (e.g. test_integration.py)

○ Low Documentation 1.0

No documentation detected

No documentation URL, doc files, or meaningful description found

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

156 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 100 commits in quantumwake/alethic-ism-db
Two distinct contributors found

🔬 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: quantumwake.io>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository quantumwake/alethic-ism-db appears legitimate

⚠ 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 alethic-ism-db

Develop a simple task management application using the 'alethic-ism-db' package, which provides a state machine framework for managing tasks based on their lifecycle states. This application will allow users to create tasks, update their status, and delete completed tasks. Here’s a detailed breakdown of the steps and features:

1. **Application Overview**: Design a user-friendly interface where users can input new tasks along with initial status (e.g., 'Pending', 'In Progress', 'Completed'). Each task should transition through these states as it progresses.

2. **Task Creation**: Implement functionality to add new tasks to the system. Each task should have a unique identifier, a description, and an initial state set to 'Pending'. Use the 'alethic-ism-db' package to define the state machine logic for transitions between states.

3. **State Transitions**: Utilize the 'alethic-ism-db' package to manage state transitions. For example, users should be able to change a task's status from 'Pending' to 'In Progress' and finally to 'Completed'. Ensure that only valid transitions are allowed according to the defined state machine.

4. **Task Deletion**: Add a feature to remove completed tasks from the system. Ensure that only tasks marked as 'Completed' can be deleted.

5. **User Interface**: Develop a basic web interface using Flask or Django to interact with the backend API built with 'alethic-ism-db'. This UI should allow users to view all tasks, update task statuses, and delete completed tasks.

6. **Database Integration**: Integrate 'alethic-ism-db' to store and manage task states efficiently. Ensure that the database supports the state machine operations required for transitioning tasks between different states.

7. **Testing**: Write tests to verify that tasks can be created, their states can be updated correctly, and only completed tasks can be deleted.

8. **Documentation**: Provide comprehensive documentation detailing how to use the application, including setup instructions, API documentation, and examples of state transitions.

By completing this project, you will gain hands-on experience with state machines, task management systems, and integrating third-party packages like 'alethic-ism-db'.