🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential risk, primarily due to sparse author metadata and possibly inactive account, though it does not conclusively indicate malicious intent.

Sparse author metadata and possibly inactive account
Expected network calls for API interaction

Per-check LLM notes

Network: Network calls are expected if the package is designed to interact with an external API.
Shell: No shell execution patterns detected.
Metadata: The author's information is sparse and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

self._session = aiohttp.ClientSession(timeout=timeout) self._external_session = Fa
else: session = aiohttp.ClientSession(timeout=timeout) try: yield sess
: self._session = aiohttp.ClientSession() self._external_session = False self._r

✓ 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: fastmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository kclif9/actronneoapi 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 actron-neo-api

Develop a user-friendly web-based dashboard using Flask and the 'actron-neo-api' package to monitor and control Actron Air Neo and Que HVAC systems. This mini-app should allow users to log in securely, view current temperature settings, adjust temperatures, switch modes (such as cooling, heating, auto), and enable/disable the system remotely.

Step-by-Step Guide:
1. Set up a basic Flask web server with user authentication (using packages like Flask-Security).
2. Integrate the 'actron-neo-api' package to connect to the Actron Air API.
3. Design simple yet intuitive HTML/CSS templates for displaying HVAC status and controls.
4. Implement routes and views to fetch real-time data from the Actron Air API and display it on the dashboard.
5. Add functionality to send commands through the 'actron-neo-api' package to change HVAC settings based on user input.
6. Ensure all interactions are secure and data is handled appropriately (e.g., using HTTPS).
7. Test the application thoroughly to ensure reliability and responsiveness.
8. Deploy the application to a cloud service provider such as Heroku or AWS.

Suggested Features:
- Real-time temperature and mode updates.
- Historical data visualization of temperature changes over time.
- Alerts for when HVAC system is turned off or reaches certain temperature thresholds.
- User preferences for customizing alerts and default settings.
- Mobile-responsive design for easy access from smartphones and tablets.