🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits unusual network activity and lacks comprehensive metadata, indicating potential risks but no concrete evidence of malicious intent.

unexpected network calls
lack of maintainer information

Per-check LLM notes

Network: The package makes unexpected network calls to localhost ports which could indicate communication with an external service or command and control server.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
Metadata: The package shows several low-effort signs and lacks important maintainer information, raising suspicion.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

8765) try: resp = urllib.request.urlopen("http://localhost:18765/api/tasks") data = j
8766) try: resp = urllib.request.urlopen("http://localhost:18766/api/tasks") data = j
8767) try: resp = urllib.request.urlopen("http://localhost:18767/api/tasks/TASK-001")
try: try: urllib.request.urlopen("http://localhost:18768/api/tasks/TASK-999")
8769) try: resp = urllib.request.urlopen("http://localhost:18769/") content = resp.re

✓ 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 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
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 agent-task-board

Create a mini-application named 'AI Task Manager' using the Python package 'agent-task-board'. This application will serve as a user-friendly interface for managing tasks assigned to AI agents, providing a visual representation of task statuses through a kanban board. Here are the steps and features to implement:

1. **Setup**: Install the required package `agent-task-board` and any additional dependencies needed for your application.
2. **User Interface**: Develop a simple web-based UI using a framework like Flask or Django. This UI should allow users to interact with the kanban board.
3. **Task Creation**: Implement functionality that allows users to create new tasks. Each task should have a title, description, and initial status (e.g., 'To Do', 'In Progress', 'Done').
4. **Kanban Board Integration**: Use the 'agent-task-board' package to integrate a kanban board into your application. This board should visually represent the tasks and their current statuses.
5. **Task Management**: Allow users to drag-and-drop tasks between columns to change their status. Additionally, provide options to edit task details and mark tasks as completed.
6. **Agent Assignment**: Integrate a feature where each task can be assigned to one or more AI agents. When a task is marked as 'In Progress', it should trigger an action (simulated or real) that sends the task to the assigned agent(s).
7. **Notifications**: Implement a notification system that alerts users when a task has been completed or when there are updates from the assigned agents.
8. **Analytics**: Provide basic analytics about the performance of the AI agents based on the tasks they handle, such as average completion time per task.

Your application should demonstrate a clear understanding of how the 'agent-task-board' package works and how it can be leveraged to enhance productivity and collaboration between human users and AI agents.