🤖 AI Analysis

Final verdict: SAFE

The package appears to be a legitimate SDK for interacting with an AI Chain service via WebSocket, with no detected malicious activities or high-risk behaviors.

No network or shell risks detected.
Potential obfuscation through base64 decoding requires further investigation but doesn't strongly indicate malicious intent.

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external API interactions.
Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
Obfuscation: Base64 decoding without clear context suggests potential obfuscation, but could also be part of legitimate data handling.
Credentials: No clear patterns indicative of credential harvesting were detected.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

4 test file(s) detected (e.g. test_connection.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (2344 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

112 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

return b"" return base64.b64decode(self.data) class WelcomeAnswerEvent(BaseEvent): ""
return b"" return base64.b64decode(self.data) class InterruptedEvent(BaseEvent): """I

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aichain-sdk

Create a mini-application that leverages the 'aichain-sdk' Python package to interact with the AI Chain platform using the IIP Dispatch WebSocket protocol v2.0. Your task is to develop a real-time chatbot that can answer questions based on pre-defined knowledge bases and also has the capability to execute simple tasks such as fetching weather information or scheduling appointments.

Step 1: Set up your development environment by installing the 'aichain-sdk' package and any other necessary libraries such as 'websocket-client'.

Step 2: Define the structure of your application. It should include classes for managing the WebSocket connection, handling incoming messages from the server, and sending requests to the AI Chain platform.

Step 3: Implement a function that connects to the AI Chain WebSocket server and authenticates your application using the appropriate credentials provided by the 'aichain-sdk'.

Step 4: Create a user interface (UI) where users can input their queries and receive responses in real-time. This UI can be a simple console application or a more advanced web-based interface using Flask or Django.

Step 5: Utilize the 'aichain-sdk' to send user queries to the AI Chain platform and process the responses. Ensure that the application can handle different types of responses, such as text, images, or links.

Step 6: Integrate additional functionalities into your chatbot, such as:
- A feature that allows users to ask for weather updates based on location data.
- An appointment scheduler that can add events to a calendar based on user instructions.
- The ability to search through a predefined knowledge base for specific answers.

Step 7: Test your application thoroughly to ensure it works correctly with the 'aichain-sdk', handles errors gracefully, and provides a smooth user experience.

By following these steps, you will have created a fully-functional mini-application that demonstrates the power of the 'aichain-sdk' package and its potential for building sophisticated applications that integrate AI capabilities.