Topics We’re Looking For:

• Autonomous red teaming
• Vulnerability discovery and exploit generation
• Cost-effective fuzzing
• Hackbots and agentic penetration testing on production systems (not CTFs)
• Agentic workflows for research and attack

• “What does an intelligent vulnerability management platform look like?”
• “how are you leveraging genai to super power your teams? not what you bought, but you solved for”
• “Real-world use of autonomous redteaming / attack simulation… my hypothesis is that redteams will become too painful once they can be run autonomously. most orgs will have too many findings to act on them”
• “AI in capture the flag, autonomous vulnerability assessments, agentic attribution”
• “AI identifying zero-day vulns”
• “Hackbots running on production systems, not CTFs. Practical examples of dynamic malware generation or c2less malware. (i.e using local models or inference endpoints to limit network comms to operator)”

Topics We’re Looking For:

• Threat detection, incident response automation, vulnerability management at scale
• Agentic systems for threat hunting, log analysis, triage
• Automated threat modeling, secure design assistance
• ROI reality check: what did AI replace vs. assist vs. make harder?
• Deepfake detection, deception as defense
• Augmenting or replacing security governance tools (audit evidence gathering, GRC automation, etc.)
• Tools your teams built internally that replaced vendors
• War stories and lessons learned

• “how are you leveraging genai to super power your teams? not what you bought, but you solved for”
• “AI tools/products/services that internal teams have built for security and or replaced vendors”
• “AI for defense (bug prevention, triage, and vulnerability response)”
• “AI ROI – measuring what AI replaced vs assisted vs made harder”
• “Scaling product security across advisory (secure system design), assessment (designing tests, scoring vulns), monitoring (onboarding logs, designing what’s important to log, not just monitoring)”
• “Effective AI for security in the SDLC (really hoping to see some talks on automated threat modeling for non-experts and cost effective fuzzing/reasoning at scale)”
• “AI Incident Response – What I am interested here is not just what they are doing from a security perspective with AI Incident Response, I am also interested in how they are working with other stakeholders, as many IR events turn into a business continuity event as well. We tabled topped this and came away with a ton of notes and issues we would need to address in a real time event”
• “Deception as defense”

Topics We’re Looking For:

• Talking to executives and boards about AI security risks and ROI
• Shadow AI: detection, management, policy that works
• Measuring what matters: benchmarks, metrics, real outcomes
• Skillsets needed and how to train non-early-adopters
• Enterprise challenges: immature tooling, lack of admin panels, configuration nightmares
• Regulatory compliance and policy navigation
• Organizational change management for AI adoption
• What are boards actually asking for?

• “I want to hear the specifics on how 2030 will look radically different from 2025. How will defense need to change because of AI powered attacks, how changing threat models shift how we architect systems.”
• “how are you speaking about enablement with other senior executive stakeholders? how are you talking about the risk?”
• “what are the skillsets of security practitioners we should be looking for? and training up for?”
• “Second order risks of AI: Beyond immediate safety issues, what unexpected system-level harms emerge once AI is scaled?”
• “what are boards asking for?”
• “how are you enabling the business (not just security?)”
• “Regulation, policy, and the messy human side of AI”
• “Real-world metrics and data backed benchmarks on cybersecurity tasks and capabilities of agents (Ex: exCyTINBench). This is a proxy for what worked for YOU instead of finger in the wind vibe science.”
• “Building the next generation of security solutions for AI-native architecture (similar to secure system design). What’s emerging and where we are in the hype cycle.”
• “Candid experiences of the ‘boring’ challenges that face enterprises in dealing with AI; from the ‘shadow ai’ to the broad array of approved tools that have immature management planes, no admin panels, integrated configurations for enterprise etc.”
• “Sharing / training – right now you have to be an earlier adopter; how have you gotten non-early-adopters to be proficient in your tools?”