AI Analysis
The package has some concerning aspects, particularly its low maintainer activity and poor metadata quality, which raise doubts about its maintenance and support. However, the direct risks like network calls and obfuscation are minimal.
- Low maintainer activity
- Poor metadata quality
Per-check LLM notes
- Network: No network calls detected.
- Shell: Shell execution is observed but seems related to task management and cloning repositories, which could be part of normal package functionality.
- Obfuscation: No obfuscation patterns detected in the provided code snippet.
- Credentials: The code attempts to retrieve a password using keyring but does not show any suspicious behavior for credential harvesting.
- Metadata: The package shows low maintainer activity and poor metadata quality, which may indicate it's not well-maintained.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (5725 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
361 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
Found 6 shell execution pattern(s)
n"] = True process = subprocess.Popen(self._worker_command(task_dir), **kwargs) return proreturn subprocess.run( ["taskkill", "/PID", str(pid), "/T", "/args.append("/F") subprocess.run( args, stdout=subprocess.DEVNULL, stp / "repo")] result = subprocess.run( clone_cmd, capture_output=True,r(project_dir)) result = subprocess.run(args) if result.returncode != 0: raise typer.Exi"" try: result = subprocess.run( ["git", "rev-parse", "HEAD"], cwd=P
Found 1 credential access pattern(s)
None: try: raw = keyring.get_password(KEYRING_SERVICE, key) except Exception as exc: l
No typosquatting candidates detected
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a command-line utility called 'TaskMaster' using the Python package 'aksesa-cli'. TaskMaster will serve as a personal task manager that allows users to manage their daily tasks efficiently. It should support adding new tasks, marking tasks as completed, listing all tasks, and deleting tasks. Additionally, it should allow users to categorize tasks into different lists (e.g., Work, Home, Personal). Each task should have a title, description, due date, and priority level. The application should also provide a feature to search for tasks based on keywords and filter tasks by category, completion status, and due date. To enhance user experience, implement a feature where users can set reminders for upcoming tasks via email notifications. This feature should use SMTP for sending emails and require the user to input their email credentials securely. Use 'aksesa-cli' to handle the command-line interface functionalities such as parsing arguments, managing subcommands, and providing help messages. Ensure the application is well-documented, including a README file that explains how to install and run the application, along with examples of common usage scenarios.
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