🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to its use of network calls and the lack of a maintainer's established online presence, including a GitHub repository.

network risk 3/10
metadata risk 4/10

Per-check LLM notes

Network: The package uses network calls to retrieve and send data, which is common but may indicate external dependency risks.
Shell: No shell execution patterns detected, suggesting low risk for direct system command injection.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has a new or inactive account and lacks a GitHub repository, raising some suspicion but not definitive proof of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

endpoint}" response = requests.get(url, headers=self._headers()) return response.json()
endpoint}" response = requests.put(url, json=payload, headers=self._headers()) response

✓ 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: acebit.se

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ 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 acemist

Imagine you are tasked with building a weather forecasting tool using Python, but with a twist - it will incorporate mystical elements to predict unusual weather phenomena. This tool, named 'WeatherWiz', will use the 'acemist' package, which, although not described, we'll assume provides unique data processing capabilities suitable for handling complex meteorological data alongside mystical variables. Your goal is to create a fully functional mini-app that allows users to input their location and receive predictions about the upcoming week's weather, including the chance of seeing unusual events like rainbow bridges or unicorn rain.

Steps to build WeatherWiz:
1. Begin by installing the necessary packages, including 'acemist'. If 'acemist' requires any dependencies, ensure those are installed as well.
2. Develop a user interface where users can enter their city or zip code. This could be a simple command-line interface or a more advanced web-based interface depending on your preference.
3. Utilize 'acemist' to fetch real-time weather data from an API (such as OpenWeatherMap) and process it alongside mystical variables (which you can define as random factors affecting the weather).
4. Implement algorithms within 'acemist' to analyze both the meteorological and mystical data to predict the likelihood of unusual weather phenomena occurring.
5. Display the results in a clear and engaging way, perhaps with colorful graphics or animations if you're developing a web-based app.
6. Add features such as saving previous forecasts, comparing current predictions with historical data, and providing explanations behind the predictions based on both meteorological science and mystical lore.
7. Ensure the application is user-friendly, with clear instructions and error messages.
8. Finally, document your code thoroughly, explaining how each part works, especially the integration of 'acemist' and its role in the mystical weather prediction system.