aod

v0.2.0 suspicious
8.0
High Risk

A descriptor for instance attributes whose values are determined on demand on first access.

πŸ€– AI Analysis

Final verdict: SUSPICIOUS

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.
  • ⚠ Typosquatting target: nox

πŸ“¦ Package Quality Overall: Low (3.4/10)

β—‹ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
β—ˆ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1725 chars)
β—‹ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
β—ˆ Medium Type Annotations 5.0

Partial type annotation coverage

  • 6 type-annotated function signatures (partial)
β—‹ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 2 commits in LivingLogic/LivingLogic.Python.aod
  • Single author with few commits β€” possibly a personal or throwaway project

πŸ”¬ Heuristic Checks

βœ“ Outbound Network Calls

No suspicious network call patterns found

βœ“ Code Obfuscation

No obfuscation patterns detected

βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 9.0

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"
βœ“ Registered Email Domain

Email domain looks legitimate: livinglogic.de>

βœ“ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Very few commits: 2 total
  • Single contributor with only 2 commit(s) β€” possibly throwaway account
⚠ 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)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with aod
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.

πŸ’¬ Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!