Mythos & Fable Can Weaponize Cyberattacks. This n8n System Fights Back
🔗 Link do vídeo: https://www.youtube.com/watch?v=LmyLXX3PEB8
🆔 ID do vídeo: LmyLXX3PEB8
📅 Publicado em: 2026-06-16T22:22:35Z
📺 Canal: n8n
⏱️ Duração (ISO): PT41M7S
⏱️ Duração formatada: 00:41:07
📊 Estatísticas:
– Views: 150
– Likes: 13
– Comentários: 1
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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.
🎙 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