AI Analysis
Final verdict: SUSPICIOUS
The package shows no immediate signs of malicious intent with low scores across network, shell, and obfuscation risks. However, the metadata risk score of 4 out of 10 due to the repository's low engagement and the author's sparse history raises some concerns about its legitimacy.
- Low engagement of the repository.
- Sparse authorship history.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
- Metadata: The repository's lack of engagement and the author's sparse history suggest potential risk.
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
Email domain looks legitimate: lut.fi>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 afsm
Create a fully-functional mini-app that simulates a simple traffic light system using the 'afsm' Python package. This app will demonstrate the use of async-aware, documentation-first Finite State Machines to manage the states of a traffic light (Red, Yellow, Green). Your task includes designing the state transitions, implementing them asynchronously, and providing a user interface to interact with the traffic light system. ### Requirements: - **State Management:** Define three main states for the traffic light: Red, Yellow, and Green. Each state should have a predefined duration before transitioning to the next state. - **Asynchronous Transitions:** Utilize the 'afsm' package to handle state transitions asynchronously, ensuring that the system can respond to external events while managing internal state changes. - **User Interface:** Implement a basic command-line interface (CLI) that allows users to manually trigger state transitions for testing purposes. - **Documentation:** Provide clear documentation on how to install and run the app, as well as a brief explanation of how the 'afsm' package is integrated into the traffic light system. ### Features: 1. **Automatic State Transitioning:** The traffic light should automatically transition from Red to Green, then to Yellow, and finally back to Red after a set period. 2. **Manual Override:** Users should be able to manually override the current state through the CLI, such as forcing the light to turn green even if it's not scheduled to do so. 3. **Event Handling:** Introduce asynchronous event handling to simulate real-world scenarios where external factors (e.g., emergency vehicles) might require immediate state changes. 4. **Logging:** Implement logging functionality to record state changes and any manual overrides for debugging and analysis purposes. ### Integration of 'afsm': - Use the 'afsm' package to define the traffic light states and their transitions. Pay special attention to how you utilize the async capabilities provided by 'afsm' to manage state changes. - Ensure that your implementation adheres to the documentation-first approach of 'afsm', clearly defining each state and transition in a structured manner.