AI Analysis
The package shows high metadata risk due to suspicious git repository activity and maintainer history, and it appears to be a typosquat targeting 'nox'. These factors strongly suggest potential malicious intent.
- High metadata risk
- Typosquatting attempt
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: High risk due to suspicious git repository activity and maintainer history.
- β Typosquatting target: nox
Package Quality Overall: Low (3.4/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (1725 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
6 type-annotated function signatures (partial)
Single-author or unverifiable project
1 unique contributor(s) across 2 commits in LivingLogic/LivingLogic.Python.aodSingle author with few commits β possibly a personal or throwaway project
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
Possible typosquat of: nox, tox, arq
"aod" is 2 edit(s) from "nox""aod" is 2 edit(s) from "tox""aod" is 2 edit(s) from "arq"
Email domain looks legitimate: livinglogic.de>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forksVery few commits: 2 totalSingle contributor with only 2 commit(s) β possibly throwaway account
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based task management application called 'On-Demand Tasks' that leverages the 'aod' package to manage tasks dynamically and efficiently. This application should allow users to add tasks with various attributes such as title, description, due date, priority level, and status (e.g., pending, completed). However, instead of loading all attributes at once, the application will use the 'aod' package to load only the necessary data on-demand when accessed. For example, if a user wants to view just the titles of their tasks, the application won't load descriptions or due dates until explicitly requested. Key Features: 1. Add new tasks with customizable attributes. 2. View tasks by title, which should load other details like description, due date, etc., only when accessed. 3. Update task statuses and attributes dynamically. 4. Utilize 'aod' descriptors to ensure efficient memory usage by deferring the loading of task details until they are needed. 5. Implement a search feature that allows users to find tasks based on specific criteria (e.g., keyword in title, due date range). 6. Provide a summary view that displays high-level information about tasks without loading full details. The application should demonstrate the flexibility and efficiency of using 'aod' descriptors by showing how it can significantly reduce the amount of data loaded into memory, especially when dealing with a large number of tasks.
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