aicqSDK

v0.8.2 suspicious
4.0
Medium Risk

AICQ AI Agent SDK — Lightweight Python SDK for AI agents to connect to AICQ server via WebSocket real-time mode (startLoop), E2EE, ephemeral rooms, stream output, temp numbers, and file transfer

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to network calls and questionable metadata, though it does not show signs of immediate malicious activity.

  • Network risk due to unverified destination URLs
  • Suspicious metadata including an anonymous author and a new/inactive account
Per-check LLM notes
  • Network: The package makes network calls which are expected for SDKs but requires further investigation to ensure the destination URLs and data being transmitted are legitimate.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows some red flags such as an author with a missing name and a new or inactive account, but there's no clear evidence of typosquatting or other malicious activities.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5132 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

  • 92 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 40 commits in ctz168/aicqSDK
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • te_key.strip() resp = requests.post(url, json=payload, timeout=30) data = resp.json()
  • _seconds + 30) resp = requests.post(url, json=payload, timeout=timeout_val) data = resp.
  • : self._session = aiohttp.ClientSession() return self._session async def _http_get(self
  • """ async with aiohttp.ClientSession() as session: url = f"{self.base_url}/api/v1/eph
  • onds + 30) async with aiohttp.ClientSession() as session: url = f"{self.base_url}/api/v1/eph
  • 册 + 登录 async with aiohttp.ClientSession() as http_session: await _ensure_registered(
✓ 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: outlook.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 aicqSDK 
Create a fully-functional mini-app called 'AI Whisperer' that leverages the 'aicqSDK' package to facilitate secure, real-time communication between users and AI agents. This app will enable users to send text messages, voice notes, and files to AI agents hosted on the AICQ server. The app should also support end-to-end encryption (E2EE) for all communications and provide temporary phone numbers for anonymous interactions. Additionally, the app should allow AI agents to stream their responses back to users in real-time. Here are the steps and features to implement:

1. **Setup and Initialization**: Begin by installing the 'aicqSDK' package and setting up your development environment with Python.
2. **User Authentication**: Implement a simple user authentication system where users can sign in or create an account.
3. **Real-Time Communication**: Utilize the WebSocket real-time mode provided by 'aicqSDK' to establish a connection between the user and the AI agent.
4. **Secure Messaging**: Ensure that all messages sent through the app are encrypted using E2EE as supported by 'aicqSDK'.
5. **File Transfer**: Allow users to upload and share files (images, documents, etc.) with AI agents. Files should also be transferred securely.
6. **Voice Notes**: Implement functionality for users to record and send voice notes to AI agents, which can then process these notes and respond appropriately.
7. **Temporary Phone Numbers**: Integrate the feature of temporary phone numbers provided by 'aicqSDK' for users who wish to communicate anonymously.
8. **Stream Output**: Enable AI agents to stream their responses back to users in real-time, enhancing the interactive experience.
9. **UI/UX Design**: Develop a user-friendly interface that makes it easy for users to interact with AI agents and manage their sessions.
10. **Testing and Deployment**: Thoroughly test the app to ensure all functionalities work as expected before deploying it to a production environment.