Agentic AI armed attackers first, but it also put real building power in defenders’ hands. Here’s what security practitioners built in two days at Black Hat USA 2026, and how the CyberAgents Exchange keeps that work compounding long after the event. Key takeaways Building defensive cybersecurity tooling no longer requires a developer. Agentic tooling drove the cost of finding and exploiting a vulnerability down to 1990s levels; it also removed the engineering barrier that kept defenders from building the automation they’ve always wanted. The unglamorous work won the room: triage, reconciliation, toil. Given two days and a requirement to publish, practitioners at SWARM developed agents for prioritization, cross-tool reconciliation, and the unglamorous toil they recognize from their own environments. All SWARM builds live on the CyberAgents Exchange , source repos attached. Every component built at SWARM is published open source with its source repository attached, so the next team facing the same problem starts from working code instead of a blank editor. Another security team already built the AI agent you need You may not realize it, but somewhere out in the ether, there’s a security team facing the same challenge as you. The only difference is they just solved the problem with agentic AI. The problem is, you have no way to find out the solution even exists. It could be an asset inventory that three systems describe in three different ways; a findings queue nobody has the hours to work; or a “critical” that a platform upgrade quietly neutralized six months ago, still sitting there waiting for someone to prove it. Somebody has already built the thing you keep meaning to build. Now it’s time we help you find it. At Black Hat USA 2026, nearly 100 registrants had the opportunity to come together for 48 hours and solve both halves of that problem: identifying a key operational pain point and building the fix. Problems like those got solved at SWARM, and the fixes are sitting on the CyberAgents Exchange right now, open source, with their source repositories attached. One team built the agent that works out which handful of fixes retires the most risk across thousands of findings. Another correlated two scanners to tell whether a flaw in the code is even reachable in the running application. A third made the case that a finding had already been mitigated, with evidence an auditor would accept. You can download and deploy any of them today. Agentic AI doesn’t just arm attackers Black Hat’s keynote stage spent this year focused on one theme: the plummeting cost of cyber offense in the agentic AI era. The price for an attacker to find and exploit a vulnerability is at lows the industry hasn’t seen since the 1990s, when a working exploit meant weeks of expert reverse engineering. Now all it takes is an afternoon and a subscription. The artisanal exploit isn’t rare anymore. True. But neither is the defender who can build. The same agentic tooling that’s arming attackers puts real building power in everyone’s hands, and that half of the story got almost no airtime. Security automation used to require the work and ongoing maintenance of skilled engineers. Now practitioners who understand the problem can build the fix. Inside the conference room at the Mandalay Bay where Tenable hosted our inaugural SWARM event, the proof of that was on every table. The winning ranking engine ships as a skill that runs on the Python standard library alone — no packages, no install step, no build pipeline. Point it at the bundled demo estate and it answers “what should we fix first?” in seconds. That’s a deliverable a practitioner can produce and a colleague can run, and two days was enough. The attacker-defender asymmetry doesn’t stem from a lack of talent or willingness. Offensive cyber capabilities compound because the tooling circulates: it’s built once, forked, passed on, or sold to the next threat actor to leverage in their attack. Meanwhile, defenders…

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