aceiot-models

v0.3.7 suspicious
4.0
Medium Risk

Pydantic models and API client for ACE IoT Aerodrome platform

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate obfuscation and metadata risks, raising suspicion about its true intentions. However, it does not exhibit any direct malicious behavior.

  • Obfuscation risk due to base64 encoding/decoding
  • Missing author information and repository
Per-check LLM notes
  • Network: The observed network patterns suggest legitimate HTTP/HTTPS request handling, which is common for many packages that interact with web services or APIs.
  • Shell: No shell execution patterns were detected, indicating no immediate risk associated with unauthorized system command execution.
  • Obfuscation: The presence of base64 decoding and encoding suggests potential obfuscation, but could also be legitimate for data handling purposes.
  • Credentials: No clear signs of credential harvesting detected.
  • Metadata: The package has a missing author name and the repository is not found, raising concerns about its legitimacy.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • logic self.session = requests.Session() self.session.headers.update( {
  • try.""" self.client = httpx.AsyncClient( timeout=httpx.Timeout(self.timeout),
  • ne: self.client = httpx.AsyncClient( timeout=httpx.Timeout(self.timeout),
  • _timeout) async with aiohttp.ClientSession(timeout=timeout) as session: for attempt in rang
⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

  • try: hash_bytes = base64.b64decode(hash_b64) return hash_bytes.hex() except
  • f it's base64 base64.b64decode(hash_value, validate=True) current_format =
  • ify it's valid base64 base64.b64decode(b64_hash) def test_encode_hash_base64_invalid_hex(self)
  • rt result != hex_hash base64.b64decode(result) def test_normalize_hash_base64_to_hex(self):
✓ 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: aceiotsolutions.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 aceiot-models 
Create a Python-based mini-application that leverages the 'aceiot-models' package to interact with the ACE IoT Aerodrome platform. Your application should serve as a monitoring tool for aerodrome operations, providing real-time data on various aspects such as flight statuses, weather conditions, and runway usage. The application will utilize Pydantic models provided by the package to structure and validate data received from the API client. Here are the key functionalities your app should include:

1. **Authentication**: Implement a login system where users can authenticate using their credentials provided by the ACE IoT Aerodrome platform.
2. **Real-Time Data Fetching**: Develop functionality to fetch real-time data about flights, including departure times, arrival times, gate numbers, and delays. Use the API client from 'aceiot-models' to make requests to the platform.
3. **Weather Updates**: Integrate weather updates specific to the aerodrome, showing current conditions and forecasts. This information should also be fetched using the API client.
4. **Runway Status**: Display the status of each runway, indicating whether they are available, under maintenance, or closed due to weather conditions.
5. **Dashboard**: Create a user-friendly dashboard that consolidates all the above information in an easily digestible format. Include charts and graphs to visualize trends over time.
6. **Alert System**: Implement an alert system that notifies users via email or SMS if there are significant changes in flight statuses or weather conditions that could affect aerodrome operations.
7. **Custom Reports**: Allow users to generate custom reports based on specific criteria, such as flights during peak hours or runway usage statistics.

To start, install the 'aceiot-models' package and explore its documentation to understand how to use its models and API client effectively. Remember to handle exceptions and errors gracefully, ensuring a smooth user experience even when faced with unexpected issues.