Agentic AI / Red Teaming

DrowAI: An AI-Assisted Red Team Platform

DrowAI helps operators create isolated attacker environments and direct an AI agent to run commands, inspect results, and organize red team work in one controlled workflow.

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Agent loop

The agent can lead, follow, or work beside the operator

DrowAI keeps the agent and operator in the same workspace. The operator can ask for direction, steer an active investigation, or let the agent propose the next move while plans, actions, and evidence stay visible.

HITL operator control

Live agent plan

Reasoning trace

Knowledge proof

Agent output becomes an inspectable attack-surface map

DrowAI turns agent activity into a connected view of the environment. Assets, services, findings, and evidence stay linked, so the operator can see what matters and why it matters.

DrowAI knowledge territory map showing network assets, services, and linked findings

Core system

A red team agent with memory, evidence, and reporting

DrowAI is built around a guided operator-agent workflow: collaborate through the task, let the system structure what the agent discovers, then use the same evidence trail to produce engagement reports.

Agent

Red Team Agent

Start from a task, question, or target context, then work with the agent in a shared loop: it can suggest next moves, explain reasoning, run checks, and adapt as the operator steers the investigation.

Knowledge

Automatic Knowledge Layer

As the agent works, DrowAI organizes collected output into linked assets, services, findings, evidence, and territory views without requiring manual bookkeeping.

Report

Agentic Engagement Reports

When an engagement is ready, DrowAI uses the collected evidence and task history to help assemble report-ready findings, context, and supporting material.

Controlled runtime

Isolated execution

DrowAI keeps agent-driven security work inside a controlled Kali container, so commands, files, observations, and task context stay visible without spilling into the operator's machine.