<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/07b1e2850b0141498e63ab24a787c529&quot; frameborder=&quot;0&quot; width=&quot;1440&quot; height=&quot;1080&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1080</height><width>1440</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1080</thumbnail_height><thumbnail_width>1440</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/07b1e2850b0141498e63ab24a787c529-983c62d825117738.gif</thumbnail_url><duration>181.868</duration><title>Closed-Loop Immunity vs Evolving Agent Attacks</title><description>This Loom explains a closed-loop defense system where attacker and defender agents evolve together to prevent unauthorized payments and other breaches. The defender detects a breach, flashes red, then generates and verifies patches without human involvement, using antibody-like updates that block new attack variations. The attacker and defense agents exchange raw traces and evolve over generations, while Band coordinates communication between separate registered agents via chat rooms and peer broadcasting for population-wide immunity. The author also describes tools used, including Senso for governed, versioned antibody records and Action with a vector database to embed attack signatures and generalize from near-neighbor matches.</description></oembed>