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ZIRAN — AI Agent Security Testing

Find vulnerabilities in AI agents — not just LLMs, but agents with tools, memory, and multi-step reasoning.


The Problem

Traditional security tools test the LLM (prompt injection, jailbreaks) or the web app (XSS, SQLi). But modern AI agents have a fundamentally different attack surface:

  • Tools that read files, query databases, and make HTTP requests
  • Memory that persists across conversations
  • Multi-step reasoning that chains tool calls together
  • Protocol endpoints (REST, OpenAI, MCP, A2A) exposed over HTTPS

An agent with read_file and http_request has a critical data exfiltration vulnerability — even if neither tool is dangerous alone. No existing tool catches this.

What ZIRAN Does

ZIRAN is the first open-source framework designed specifically for agent security testing:

Core Capabilities

  • 🔗 Tool Chain Analysis — Automatically detects dangerous tool combinations across 30+ known patterns
  • 🛡 Multi-Phase Trust Exploitation — Progressive campaigns that build trust before testing boundaries
  • 🌐 Remote Agent Scanning — Test any published agent over HTTPS (REST, OpenAI, MCP, A2A)
  • 🗺 Knowledge Graph — Every capability, relationship, and attack path tracked in a live graph
  • 📊 CI/CD Quality Gate — Block deployments that fail security thresholds, with SARIF output
  • 🔍 Static Analysis — Scan agent source code for vulnerabilities without running the agent

Quick Demo

pip install ziran
git clone https://github.com/taoq-ai/ziran.git && cd ziran
uv sync --extra langchain

# Scan a vulnerable example agent
uv run python examples/10-vulnerable-agent/main.py

How It Compares

Capability ZIRAN Garak Promptfoo PyRIT Shannon
Agent-aware (tools + memory) Yes Partial
Tool chain analysis Yes
Multi-phase campaigns Yes Partial Yes
Knowledge graph tracking Yes
Remote agent scanning (HTTPS) Yes REST only HTTP provider Partial
Multi-protocol (REST/OpenAI/MCP/A2A) Yes
A2A protocol support Yes
CI/CD quality gate Yes Yes Pro

Next Steps