AI Analysis
Final verdict: SAFE
The package shows very low risk across all assessed categories. With no detected network calls, shell executions, obfuscations, or credential harvesting attempts, it appears safe from immediate threats. The metadata risk slightly increases due to the maintainer having only one package.
- Low risk in network, shell, and obfuscation categories
- Single package maintained by the author
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
- Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
- Metadata: The maintainer has only one package, which could indicate a new or less active account.
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: gmail.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository wakatime/wakaq appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Alan Hamlett" 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 WakaQ
Create a real-time data processing application using the 'WakaQ' package in Python. This application will simulate a simple IoT device monitoring system where multiple sensors send data to a central server. The server processes this data asynchronously using WakaQ to handle background tasks efficiently. ### Project Overview: - **Application Name:** SensorDataProcessor - **Goal:** To demonstrate real-time data handling and asynchronous processing using WakaQ. ### Key Features: 1. **Sensor Data Simulation:** Simulate incoming sensor data from various devices. Each device sends a unique identifier and sensor reading. 2. **Asynchronous Processing:** Use WakaQ to process each incoming data point asynchronously. Tasks include calculating average values over time, detecting anomalies, etc. 3. **Real-Time Alerts:** If certain thresholds are exceeded (e.g., temperature too high), trigger an alert notification via email or SMS. 4. **Dashboard Interface:** Develop a basic web interface to display processed data in real-time, including charts for visual representation of trends. ### Steps to Build the Application: 1. **Setup Environment:** Install necessary Python packages, including WakaQ, Flask (for web interface), and any other required libraries. 2. **Data Simulation:** Create a script that simulates sending sensor data to the server at regular intervals. 3. **Task Queue Setup:** Configure WakaQ to set up a task queue that listens for incoming data and processes it asynchronously. 4. **Processing Logic:** Implement logic within the worker tasks to perform operations like averaging, anomaly detection, etc. 5. **Alert System:** Integrate an alert mechanism that triggers based on specific conditions detected during data processing. 6. **Web Interface:** Develop a simple dashboard using Flask to visualize the processed data in real-time. 7. **Testing & Deployment:** Test the application thoroughly and deploy it to a cloud environment for continuous operation. ### Utilizing WakaQ: - Use WakaQ to manage the task queue efficiently, ensuring that each incoming data point is processed without blocking the main application thread. - Leverage WakaQ's capabilities to scale processing as more devices connect and send data. - Ensure that tasks are retried if they fail and that the system remains robust against failures.