Find Your Zero-Days Before an Autonomous Attacker Does
Join Nahid Farady, PhD (Principal Tech Lead, AI Security & Privacy · Microsoft) for a free live session.
Nahid Farady, PhD
Principal Tech Lead, AI Security & Privacy · Microsoft
⭐ 4.9 / 5
Find your zero-days before an autonomous attacker does.
Mythos found a 17-year-old FreeBSD flaw and built a working exploit in hours. It surfaced 2,000+ unknown vulnerabilities in seven weeks. Your traditional vuln management cycle measures itself in months. The math doesn't work anymore. This sprint is for security leaders whose defensive cycle has to compress — fast — to match an attacker that operates at machine speed, never tires, and chains exploits autonomously. In 6 weeks, you'll build the defensive capability that doesn't exist as a discipline yet: running offensive AI against your own code and infrastructure before adversaries do.
What You'll Learn
AI-Attacker Threat Model
Map the autonomous-attacker lifecycle against your environment. Identify which assets, legacy systems, and third-party paths compress hardest under machine-speed attack. The reusable starting document for every Mythos-era security review.
Defensive AI for Your Codebase
Run offensive AI tools against your own code, dependencies, and infrastructure. Build a continuous self-attack pipeline. Discover your zero-days before adversaries get the same tools.
Compressed-Cycle Vulnerability Management
Redesign vuln management for a disclosure-to-exploit window measured in hours. Patch pipeline automation, virtual patching for unpatchable critical infra, SBOM hygiene, and dependency monitoring.
Machine-Speed Detection and Response
Behavioral detection for novel exploits, AI-augmented log triage, pre-authorized automated containment, and IR playbooks tabletoped against simulated AI-attacker scenarios.
Who Is This For?
This sprint is designed for:
Security Architects and Leads at Critical Infra Orgs
Energy, utilities, manufacturing, water, transportation, finance — sectors with significant operational technology exposure where CISA has explicitly flagged the AI-attacker risk as material.
Vulnerability Management Leads
Who own SLAs designed for a 30/60/90-day patch cycle now sized against a threat that compresses to hours. This sprint rewrites the job description.
Security Engineering Leads / Deputy CISOs
Who need to brief their CISO and board on what they're doing about autonomous attackers and don't currently have a defensible answer. Leave with a board-ready plan, not a vendor RFP.
Sprint Outline
6 weeks · 3 sessions per week
Projects You'll Ship
Leave with real work to show, not just a certificate.
AI-Attacker Threat Model + Defensive Stack Audit
Your full environment mapped against autonomous-attacker TTPs, with a prioritized list of structural gaps. Becomes the standard input to every security review your org runs going forward.
Defensive AI Pipeline (Self-Attack Loop)
Open-source offensive AI tools running continuously against your own code and dependencies, integrated into CI/CD, with findings triaged and routed. A working self-attack pipeline you keep running after the cohort.
Mythos-Era Defense Playbook
Vuln management SLA redesigned for hours. Machine-speed detection rules deployed. IR playbook tabletoped against a simulated AI attacker. A board-ready, defensible answer to 'what is our plan against autonomous adversaries.'
Your Instructors
Nahid Farady, PhD
Principal Tech Lead, AI Security & Privacy · Microsoft
⭐ 4.9 / 5
Nahid leads AI security, privacy, and responsible AI engineering at Microsoft Copilot, with prior roles at Google Cloud and Capital One CyberML. She holds a PhD from Virginia Tech and brings 10+ years of applied experience in cybersecurity, threat modeling, and ML deployment at scale. She also teaches AI and security as adjunct faculty at UC Berkeley.
What Students Say
⭐⭐⭐⭐⭐
"Week 2's self-attack pipeline is now running in our CI/CD permanently. We found three dependency vulnerabilities in the first month that our traditional scanner missed entirely."
Marcus Chen
Security Architect · JPMorgan Chase
⭐⭐⭐⭐⭐
"The board presentation from Week 6 is the first time our CISO felt we had a real answer to the autonomous attacker question. We walked out with budget approved."
Sarah Okafor
Deputy CISO · Constellation Energy
⭐⭐⭐⭐⭐
"The tabletop in Week 5 against a simulated AI attacker exposed three gaps in our IR playbook we had no idea existed. We've since closed all three."
Derek Walsh
Head of Vulnerability Management · Lockheed Martin
Sprint Schedule
All sessions are instructor-led and live. Recordings available within 24 hours.
SUNDAY
9:00 AM PDT
Live ClassDeep dive with live attack labs, war games, and threat modeling exercises. Offensive and defensive every week.
WEDNESDAY
6:00 PM PDT
Lab SessionStructured attack or defense lab with instructor guidance. Bring your environment, your findings, your blockers.
THURSDAY
6:00 PM PDT
Build & ShipBuild and pressure-test your weekly deliverable. Peer review before submission.
Frequently Asked Questions
Find Your Zero-Days Before an Autonomous Attacker Does
with Nahid Farady, PhD · Principal Tech Lead, AI Security & Privacy, Microsoft
What you'll walk away with:
🎁 Bonus for attendees:
Get "The Autonomous Attacker Defense Starter Kit"
Mythos-era threat model template + self-attack tool list + compressed-cycle vuln management SLA framework
Claim your free seat
Skills you can deploy on Monday morning.