🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits some unusual characteristics, particularly the shell execution capability and the metadata indicating a potentially new or less active maintainer.

Shell risk detected
Low maintainer activity

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: The detection of shell execution suggests the package may execute commands, which could be legitimate depending on its purpose but warrants further investigation to ensure it's not being used maliciously.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
Metadata: The maintainer has a new or inactive account with minimal package history and no author name, which may indicate low activity or oversight.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

4 test file(s) detected (e.g. test_hooks.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (2124 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

54 type-annotated function signatures detected in source

✦ High Multiple Contributors 8.0

Active multi-contributor project

3 unique contributor(s) across 100 commits in Vizonex/aiocallback
Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

one: try: subprocess.run( [self.get_bin()] + self.CMD,

✓ 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

Repository Vizonex/aiocallback appears legitimate

⚠ 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)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aiocallback

Create a mini-application called 'AsyncWatcher' that monitors file changes in real-time and triggers specific actions based on those changes. This application will utilize the Python package 'aiocallback' to manage asynchronous callbacks efficiently. Here's a detailed breakdown of what the application should do and how you can use 'aiocallback' to achieve its goals:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the 'watchdog' library for monitoring file system events and 'aiocallback' for managing asynchronous callbacks.

2. **Application Structure**: Design your application to have two main components - a file watcher and a callback handler. The file watcher will monitor specified directories for any changes, while the callback handler will define actions to take when these changes occur.

3. **File Watcher**: Implement a class named `FileSystemWatcher` that uses the `watchdog` library to watch for changes in files and directories. This class should accept directory paths as input and start watching them for changes such as creation, modification, deletion, etc.

4. **Callback Handler**: Use the `aiocallback` package to define asynchronous callback methods that get triggered when specific file system events are detected. These callbacks should be member descriptors managed by 'aiocallback', allowing for clean and efficient handling of asynchronous operations.

5. **Actions Based on Events**: Define various actions that the application should perform based on different types of file system events. For example, if a file is modified, the application could print a log message; if a file is deleted, it could notify the user via email or another notification service.

6. **Configuration Interface**: Provide a simple configuration interface where users can specify which directories to watch and what actions to take for each type of event. This can be done through command-line arguments or a basic GUI.

7. **Testing and Validation**: Finally, thoroughly test your application to ensure it correctly identifies file system changes and executes the appropriate actions. Validate its performance under various conditions, including high-frequency file changes.

In this project, the 'aiocallback' package plays a crucial role in defining and managing asynchronous callbacks. By leveraging 'aiocallback', you ensure that your application remains responsive and performs optimally even when handling multiple concurrent file change events.