Get the open-source incident response workflow here: https://go.n8n.io/incident-response
Anthropic's Mythos AI just found a 27-year-old security bug in OpenBSD that no human ever caught. Days later the US government pulled both Mythos 5 and the public Fable 5 model, worried that same power could be weaponized into cyberattacks. The threat is no longer theoretical, and if your defense isn't automated too, you're already behind.
Dylan sits down with Viraj, a former n8n team member turned forward-deployed engineer, who now helps enterprise companies build AI-powered security systems. They walk through a live demo of an open-source cybersecurity workflow built with n8n and backed by real incident data.
The conversation covers how to bring AI into SecOps without letting it run wild, why historical incident data and playbooks matter more than the model you choose, and how Anthropic's Mythos is changing the threat landscape by chaining multiple vulnerabilities in a single attack. They also dig into real-world social engineering scams, phishing tactics, and why good data hygiene is the unsexy foundation that makes any AI system actually work.
The bigger takeaway: the models will keep getting smarter, but the companies (and individuals) who win are the ones with clean data, solid playbooks, and a workflow harness that can plug in whatever model comes next. This is a practical blueprint for fighting AI-powered threats with your own AI-powered defense.
đ Chapters: 00:00 - AI Found a 27-Year-Old Bug 00:37 - What the Demo Covers 02:43 - Test Incidents, Playbooks & Data 06:11 - Live Phishing Workflow Demo 07:08 - Three Branches of Analysis 09:35 - Threat Intelligence Explained 12:31 - Mythos and Zero-Day Threats 15:20 - Why Data Hygiene Matters 16:36 - Workflow Results Walkthrough 21:07 - Social Engineering and Scams 25:07 - Actionable Remediation Steps 30:53 - Data Ingestion for Companies 34:50 - Forward-Deployed Engineering 38:51 - Local Models and Personal Security 40:41 - Where to Find Viraj
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