AI Analysis
Final verdict: SAFE
The package shows low risks across all evaluated categories except metadata, where there are some concerns about the completeness of the author's information and the maintainer's activity level. However, these factors alone do not indicate malicious intent.
- Low risk scores in network, shell, obfuscation, and credential areas.
- Concerns about incomplete author information and potential inactivity of the maintainer.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires them for functionality.
- Shell: No shell execution detected, indicating no immediate risk of command injection or similar attacks.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author's information is incomplete and the maintainer seems new or inactive, raising some concerns but not definitive evidence 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
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 aa-taskmonitor
Your task is to develop a real-time task monitoring web application using Flask as the web framework and the 'aa-taskmonitor' package to integrate with an existing Alliance Auth system. This application will allow users to monitor the status of their background tasks processed by Celery. The application should include the following core functionalities: 1. User Authentication: Users must log in through the Alliance Auth system before accessing the task monitoring interface. 2. Task List Display: Upon logging in, users should see a list of all their pending, running, and completed tasks. Each task entry should include the task ID, start time, end time (if completed), current status, and estimated completion time (ETA). 3. Detailed Task View: Clicking on a specific task should provide more detailed information about its progress, including any error messages if the task failed. 4. Real-Time Updates: The task list should refresh automatically every few seconds to reflect any changes in task status without requiring a page reload. 5. Search Functionality: Implement a search bar where users can filter tasks based on keywords from the task description or task IDs. 6. Task Cancellation: Allow users to cancel running tasks directly from the task monitoring interface. 7. Notifications: Integrate a notification system that alerts users via email or push notifications when a task completes or fails. 8. Dashboard: Create a dashboard that provides an overview of the userβs task activity over time, such as graphs showing task completion rates and average task durations. To achieve these functionalities, you will need to utilize the 'aa-taskmonitor' package effectively. Specifically, you will use it to authenticate users against the Alliance Auth system, retrieve task information from the Celery backend, and handle task cancellation requests. Additionally, you should ensure that your application is secure, efficient, and user-friendly.