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EpisodeMonday, July 6, 2026 · 18 min
$episode№064·date2026-07-06·duration18 min·turns131

New Research Exposes a Blast-Radius Problem in Multi-Agent AI Systems

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New Research Exposes a Blast-Radius Problem in Multi-Agent AI Systems
9 sources · quality 4/5

A new paper on multi-agent AI security reveals a blast-radius problem that applies directly to agentic NetOps pipelines, including, we admit, our own. Plus a vendor fabric pitch that's really an automation story, a black hole that shouldn't exist, and a device that talks in sound instead of light.

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131 turns · ~14 min read
HOST A

Welcome to Amaze Networks for Monday, July sixth. Quick question to open the week. If you're running a pipeline of AI agents that all feed into each other, how many of them would an attacker actually need to compromise to take the whole thing down? There's a paper out today that answers that, and it hits closer to home than we'd like.

HOST B

Closer to home is right. Let's get into it.

HOST A

This is a new arXiv preprint, and the setup is simple. In a network of AI agents passing work to each other, not every agent matters equally. Some of them sit at a chokepoint where a lot of other agents depend on their output.

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