AI Analysis
Final verdict: SUSPICIOUS
The package has minimal risks in terms of network, shell, and obfuscation activities. However, the metadata quality concerns and low maintainer activity raise suspicions about its integrity.
- Low maintainer activity
- Poor metadata quality
Per-check LLM notes
- Network: No network calls suggest normal behavior unless specific features require external services.
- Shell: No shell execution detected, indicating no immediate risk of command injection or unauthorized access.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (4.4/10)
✦ High
Test Suite
9.0
Test suite present — 2 test file(s) found
Test runner config found: pyproject.toml2 test file(s) detected (e.g. test_engine.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (7682 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
67 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
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)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with alarmdb
Create a home automation system using the Python package 'alarmdb'. This system will allow users to manage their smart home devices such as lights, thermostats, and security systems through a command-line interface. The application should enable users to set up alarms for various events (e.g., turning off all lights at midnight, setting the thermostat to a certain temperature at specific times), view current statuses of connected devices, and receive notifications when certain conditions are met. Core Features: - User authentication for secure access. - Device management: add, remove, and update devices. - Alarm creation: specify time, device actions, and conditions. - Real-time status updates for all connected devices. - Notification system for alerts and updates. The 'alarmdb' package will be utilized to store and manage all the data related to alarms and device statuses. It will provide a robust database layer that supports efficient querying and updating of records. For instance, you could use 'alarmdb' to efficiently retrieve all alarms that need to be executed at a specific time or to update the status of a device after it has been manipulated through the application. Your task is to design and implement this system from scratch, ensuring that it is user-friendly, scalable, and reliable. Additionally, write comprehensive documentation and examples to help other developers understand how to integrate 'alarmdb' into their own projects.
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