🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some unusual behavior with the use of git commands, which raises suspicion about its legitimate purpose. However, there are no clear signs of malicious activities.

shell risk due to usage of git commands
low activity maintainer

Per-check LLM notes

Network: No network calls detected, which is normal and does not indicate any risk.
Shell: The use of git commands suggests the package may be setting up or testing Git repositories locally, which could be part of its functionality but requires further investigation to confirm legitimacy.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
Metadata: The maintainer has only one package, which might indicate a new or less active account, but no other red flags were identified.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

Test runner config found: pyproject.toml
12 test file(s) detected (e.g. test_bridge.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (5921 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

121 type-annotated function signatures detected in source

✦ High Multiple Contributors 8.0

Active multi-contributor project

4 unique contributor(s) across 67 commits in htkuan/ai-agent-bridge
Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

set. try: subprocess.run( ["git", "symbolic-ref", "refs/remotes/origi
path: Path, monkeypatch): subprocess.run(["git", "init", "-q", str(tmp_path)], check=True) monkey
repo = tmp_path / "repo" subprocess.run(["git", "init", "-q", "-b", "main", str(repo)], check=True)
, str(repo)], check=True) subprocess.run(["git", "-C", str(repo), "config", "user.email", "t@t"], che
ail", "t@t"], check=True) subprocess.run(["git", "-C", str(repo), "config", "user.name", "t"], check=
.name", "t"], check=True) subprocess.run( ["git", "-C", str(repo), "commit", "--allow-empty",

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository htkuan/ai-agent-bridge appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "htkuan" 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 ai-agent-bridge

Create a real-time chatbot integration tool called 'ChatBridge' that allows users to connect multiple chat platforms (such as Slack, Discord, and Telegram) with various AI agents (like LangChain, Anthropic Claude, or Anthropic Claude API). Your task is to design and implement a fully functional mini-app using the Python package 'ai-agent-bridge'. This app will serve as a modular interface that translates messages from one platform's format to another, enabling seamless communication between different chat systems and AI agents.

Step 1: Set up the project structure and install necessary dependencies including 'ai-agent-bridge', 'slack-sdk', 'discord.py', and 'python-telegram-bot'.

Step 2: Define a modular architecture where each module represents a chat platform or an AI agent. Each module should include functions to authenticate with the respective service, handle incoming messages, and send responses back.

Step 3: Implement a message router that takes incoming messages from any connected chat platform, processes them through the appropriate AI agent based on predefined rules, and then sends the response back to the original chat platform.

Suggested Features:
- User-friendly web interface for adding new chat platforms and AI agents.
- Support for customizing message routing rules.
- Logging of all interactions for debugging and analytics purposes.
- Ability to pause/resume individual connections or entire bridges.

The 'ai-agent-bridge' package should be utilized extensively throughout the project. It provides the foundational framework for connecting chat platforms and AI agents, handling message formats, and ensuring smooth operation. Use its modular design to quickly add support for new services without significant changes to the core logic.