aiscat

v0.68.12 suspicious
4.0
Medium Risk

Fast, complete AIS NMEA decoder for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate network activity which could be legitimate but warrants further investigation. Additionally, the metadata suggests a less trustworthy maintainer, increasing suspicion.

  • moderate network risk
  • low trustworthiness due to maintainer metadata
Per-check LLM notes
  • Network: The network calls may be legitimate if the package is designed to send or receive data from remote servers.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate a lower level of trustworthiness.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_decode.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (16827 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

  • Type checker (mypy / pyright / pytype) referenced in project
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in jvde-github/AIS-catcher
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • dst_host, dst_port): with socket.create_connection((dst_host, dst_port)) as sink: for packet in aiscat.
  • at, country=country) with socket.create_connection((host, port), timeout=timeout) as sock: while True:
✓ 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 jvde-github/AIS-catcher 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 aiscat 
Create a real-time maritime tracking application using the 'aiscat' Python package. This application will decode and display live Automatic Identification System (AIS) data transmitted by ships. Here’s a detailed plan on how to build this application:

1. **Setup Environment**: Begin by setting up your Python environment. Install necessary packages including 'aiscat' which you'll use for decoding AIS NMEA messages.
2. **Fetch Data**: Integrate an API or source that provides live AIS NMEA data streams. Popular options include MarineTraffic or AIS Hub.
3. **Decode Messages**: Use 'aiscat' to decode the incoming NMEA messages into structured data. Focus on extracting essential information such as vessel ID, position, course, speed, and time.
4. **Display Information**: Design a user interface that displays the decoded information in a readable format. Consider using libraries like PyQt5 or Tkinter for GUI development.
5. **Real-Time Updates**: Ensure the application updates the displayed information in real-time as new AIS messages are received.
6. **Additional Features**:
   - Implement a map visualization using a library like Folium or Pygame to show the current positions of the vessels.
   - Include filters to allow users to select specific types of vessels based on their MMSI number or vessel type.
   - Add alerts for when a vessel enters a predefined area or crosses a certain threshold in speed or direction.
7. **Testing & Deployment**: Test the application thoroughly under different scenarios to ensure reliability and accuracy. Once satisfied, consider deploying it as a web app or desktop application.

This project aims to showcase the capabilities of 'aiscat' while providing a practical tool for monitoring maritime traffic.

💬 Discussion Feed

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