🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activities such as network calls, shell executions, or credential harvesting. However, the metadata suggests it may be from a new or less active developer.

No network calls
No shell executions
No obfuscation
No credential harvesting
Single package from the author

Per-check LLM notes

Network: No network calls suggest normal behavior unless the package's purpose inherently requires them.
Shell: No shell executions indicate that the package does not attempt to execute system commands without user interaction.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
Metadata: The author has only one package on PyPI, which might indicate a new or less active account.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://docs.investigraph.dev/lib/anystore
Detailed PyPI description (5630 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 7.0

Partial type annotation coverage

Type checker (mypy / pyright / pytype) referenced in project
221 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 100 commits in dataresearchcenter/anystore
Two distinct contributors found

🔬 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 score 3.0

Suspicious email domain flags: Very short email domain: pm.me

Very short email domain: pm.me

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository dataresearchcenter/anystore appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Simon Wörpel" 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 anystore

Create a personal task manager application using Python that leverages the 'anystore' package for storing and caching tasks. This application should allow users to add, delete, update, and view their tasks. Additionally, it should support tagging tasks with categories such as 'Work', 'Home', 'Study', etc., and provide filtering options based on these tags.

The application should have the following functionalities:
1. Add Task: Users can input a new task along with its description and tags.
2. View Tasks: Display all tasks in a user-friendly format, including their descriptions and associated tags.
3. Update Task: Modify any aspect of a task, including its description or tags.
4. Delete Task: Remove a specific task from the system.
5. Filter Tasks: Allow users to filter tasks based on their tags.
6. Caching: Implement caching mechanisms to speed up repeated access to frequently viewed tasks.
7. Persistence: Ensure that tasks persist across sessions, meaning that when the application restarts, all previously added tasks should still be available.

Use the 'anystore' package to manage storage and caching operations. Consider scenarios where tasks might need to be stored locally, remotely, or in a hybrid manner, showcasing the flexibility provided by 'anystore'.

Your task is to design and implement this application, detailing how each feature interacts with the 'anystore' package to achieve efficient and reliable task management.