🧠 AgentNull: AI System Security Threat Catalog + Proof-of-Concepts
About
AgentNull: AI System Security Threat Catalog + Proof-of-Concepts. Collection of PoCs for using Agents, MCP, and RAG in bad ways.
Details
- Author
- jaschadub
- GitHub stars
- 3
- Downloads
- 504
- Categories
- Developer Tools, AI, Security
Jump to
- Catalog contains attack vectors for AI agents, RAG, vector databases, and embeddings.
- Each attack vector includes its own README, code, and sample input/output.
- Structured JSON catalog available for SOC/SIEM ingestion.
- Novel starred (⭐) attack concepts developed primarily within the AgentNull project.
- Supports local LLM testing via Ollama for cost-free demonstrations.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
🧠 AgentNull: AI System Security Threat Catalog + Proof-of-ConceptsCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Navigate into each pocs/<attack_name>/ folder and follow its README to replicate the attack scenario. For enhanced PoC demonstrations without API costs, use Ollama with local models (e.g., ollama pull gemma3), then run PoCs with python3 advanced_tool_poisoning_agent.py local or simulation mode.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"\ud83e\udde0 agentnull: ai system security threat catalog + proof-of-concepts": {
"AgentNull": {
"command": "python3",
"args": [
"advanced_tool_poisoning_agent.py",
"local"
]
}
}
}
}McpServers
{
"AgentNull": {
"command": "python3",
"args": [
"advanced_tool_poisoning_agent.py",
"local"
]
}
}🧠 AgentNull: AI System Security Threat Catalog + Proof-of-Concepts
This repository contains a red team-oriented catalog of attack vectors targeting AI systems including autonomous agents (MCP, LangGraph, AutoGPT), RAG pipelines, vector databases, and embedding-based retrieval systems, along with individual proof-of-concepts (PoCs) for each.
📘 Structure
- catalog/AgentNull_Catalog.md — Human-readable threat catalog
- catalog/AgentNull_Catalog.json — Structured version for SOC/SIEM ingestion
- pocs/ — One directory per attack vector, each with its own README, code, and sample input/output
⚠️ Disclaimer
This repository is for educational and internal security research purposes only. Do not deploy any techniques or code herein in production or against systems you do not own or have explicit authorization to test.
🔧 Usage
Navigate into each pocs/<attack_name>/ folder and follow the README to replicate the attack scenario.
🤖 Testing with Local LLMs (Recommended)
For enhanced PoC demonstrations without API costs, use Ollama with local models:
Install Ollama
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