🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential obfuscation techniques that could be used for malicious purposes, despite showing no direct signs of harmful behavior or credential theft.

Obfuscation risk at 7/10
Lack of clear malicious intent but presence of obfuscation techniques

Per-check LLM notes

Network: The observed network calls are likely legitimate if the package is intended to perform HTTP requests for its functionality.
Shell: No shell execution patterns were detected.
Obfuscation: The code shows signs of obfuscation through base64 encoding, which can be used for malicious purposes such as hiding code or data.
Credentials: No clear patterns indicative of credential harvesting were found in the provided snippet.
Metadata: The package shows some red flags but lacks clear evidence of malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

= user_id async with httpx.AsyncClient(timeout=self._timeout_seconds) as client: respon
} async with httpx.AsyncClient(timeout=timeout_seconds) as client: try:
= user_id async with httpx.AsyncClient(timeout=self._timeout_seconds) as client: resp =

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

: {mime}") image_bytes = base64.b64decode(b64_data) return mime, image_bytes def _resolve_save_d

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:8000/api/chat

✓ 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 MA-Agent

Your task is to create a Feishu-based chatbot named 'FeiBot' using the MA-Agent Python package. This chatbot will serve as a versatile tool for Feishu users, integrating various functionalities through its modular design. The primary goal of FeiBot is to provide quick access to information, automate routine tasks, and enhance collaboration within teams. Here’s a detailed plan on how to approach this project:

1. **Setup Environment**: Begin by setting up your development environment. Install Python and necessary libraries including MA-Agent. Ensure you have a Feishu app registered with the appropriate permissions.

2. **Initialize Project Structure**: Create a project directory for FeiBot. Within this directory, initialize a virtual environment and install MA-Agent via pip. Set up basic project files such as main.py, config.py, and a plugins directory for extending functionality.

3. **Configure FeiBot**: Use MA-Agent to configure FeiBot with your Feishu app credentials. Implement authentication and authorization mechanisms to ensure secure communication between FeiBot and Feishu API endpoints.

4. **Develop Core Features**: Utilize MA-Agent's capabilities to develop core functionalities for FeiBot. These include:
- **User Interaction**: Enable FeiBot to respond to user messages in real-time. Implement natural language processing to understand and respond appropriately to commands and inquiries.
- **Task Automation**: Integrate scripts or APIs to automate common tasks like scheduling meetings, sending reminders, or managing tasks.
- **Information Retrieval**: Allow FeiBot to fetch and present relevant data from various sources such as calendars, databases, or external APIs.

5. **Extend Functionality with Plugins**: Leverage MA-Agent’s pluggable architecture to add new features without modifying the core codebase. For instance, you could develop a plugin that integrates with weather APIs to provide daily weather updates or another that connects to news feeds for the latest headlines.

6. **Testing and Deployment**: Thoroughly test FeiBot’s functionalities in a staging environment before deploying it to production. Monitor performance and user feedback to make necessary adjustments.

7. **Documentation and Support**: Provide comprehensive documentation detailing setup instructions, configuration options, and usage examples. Establish support channels for users to report issues and request enhancements.

Throughout the development process, utilize MA-Agent’s features to streamline integration with Feishu’s ecosystem and ensure a seamless user experience. Your final product should demonstrate proficiency in leveraging MA-Agent’s capabilities while offering valuable services to Feishu users.