Demos

3 minutes. That’s all it takes to red team your AI agent

3 minutes. That’s all it takes to red team your AI agent

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What happens when you turn a swarm of adversarial agents loose on your AI app? In this walkthrough, I take Darkhunt for a spin against a live AI agent – no custom scripts, no manual prompt engineering, just point-and-shoot red teaming that surfaces real vulnerabilities in minutes.

Summary

  • Two-Click Connection – Connect your AI app via dashboard URL or install the CLI for deeper integration with your own stack

  • Adversarial Swarm – Run in parallel against your endpoint, each targeting a distinct class of LLM weakness

  • Live Probe Monitoring – Watch every prompt, response, and verdict stream in as the attack unfolds – no waiting for a final report

  • Attack Taxonomy – Every probe is mapped to a category (prompt injection, jailbreak, data exfiltration, tool abuse, system prompt leak), so you know exactly what was tested and what broke

  • Caught vs. Survived – Each session ends with a clear scoreboard: how many attacks your model resisted, how many it fell for, and which probes need a closer look

  • Compliance-Ready Output – Findings export cleanly into the formats your security and audit teams already use

Runtime supervision for AI agents. Darkhunt checks every step your agents take and catches the ones that don’t fit the task.

Runtime supervision for AI agents. Darkhunt checks every step your agents take and catches the ones that don’t fit the task.

Runtime supervision for AI agents. Darkhunt checks every step your agents take and catches the ones that don’t fit the task.