Day 1 | Stage 2

Chief of Forensics/Malware Analysis from U.S. Army Cyber Command discusses the Army's path to enterprise AI showing deployment constraints shape adoption more than security policies. Covers 2023's fragmented research previews (high innovation but no institutional knowledge), 2024's centralized solutions (killed experimentation), and 2025's enterprise agreements (now grappling with cultural change convincing people the tool is actually usable).

Chase Hasbrouck is Chief of Forensics/Malware Analysis, U.S. Army Cyber Command.

Watch on YouTube: https://www.youtube.com/watch?v=UOtVmYR0mRg

Day 1 | Stage 2

Chief AI Officer from SANS Institute explains wiring agentic AI into SIFT via Model Context Protocol—timeline generation, memory analysis, malware sweeps, all via natural language. References Anthropic's GTG-1002 report showing adversaries running Claude Code at 80-90% autonomous execution. Shows live demo where typing "SIFT!! Find Evil!" actually works. Based on 40+ hours of testing.

Rob T. Lee is Chief AI Officer (CAIO) and Chief of Research, SANS Institute.

Watch on YouTube: https://www.youtube.com/watch?v=OsUg3TlAqjQ

Day 1 | Stage 2

Threat Research & Detection Engineer from Elastic explores GenAI endpoint observability from a practitioner's perspective. As GenAI coding assistants become standard developer tools, detection engineers face challenges understanding what happens when AI executes commands on behalf of users. Discusses what telemetry exists, where gaps are, and why standardized schemas for AI activity are needed.

Mika Ayenson is Threat Research & Detection Engineer, Elastic.

Watch on YouTube: https://www.youtube.com/watch?v=cEbPSQaSLXM

Day 1 | Stage 2

Sr Principal Researcher from Palo Alto Networks introduces SYARA (Super YARA), extending YARA's syntax with multi-modal semantic detection. Combines string matching, embeddings, ML classifiers, and LLMs in a single rule. Teaches hunting for GenAI-era threats including prompt injection, phishing, malicious intent identification, and disinformation detection, achieving 98% detection rates.

Mohamed Nabeel is Sr Principal Researcher, Palo Alto Networks.

Watch on YouTube: https://www.youtube.com/watch?v=PZYtJL6TCwo

Day 1 | Stage 2

Principal Offensive AI Security Researchers from NVIDIA discuss Marinade, an agentic workflow solving the problem of getting realistic vulnerable applications. Analyzes codebases (Django, Spring Boot, Java, Rails), understands attack surface, and injects realistic, exploitable vulnerabilities that blend naturally into existing code. AI is surprisingly adept at weakening security controls rather than clumsily removing them.

Aaron Grattafiori is Principal Offensive AI Security Researcher, NVIDIA.

Skyler Bingham is Principal Applied Researcher, NVIDIA.

Watch on YouTube: https://www.youtube.com/watch?v=nRH_rdW7EL8

Day 1 | Stage 2

CTO and Cofounder of Sondera demonstrates a reference monitor using Rust hooks and Cedar policies to deterministically intercept every shell command, file read, and other actions. Coding agents wield dangerous access to code and terminal, and prompt injection renders soft guardrails useless. Live demo forbids exfiltration and destructive behaviors with open-source tool compatible with Cursor, Claude Code, and GitHub Copilot CLI.

Matt Maisel is CTO and Cofounder, Sondera.

Watch on YouTube: https://www.youtube.com/watch?v=m6pzrqFJ6hE

Day 1 | Stage 2

Co-Founder & CTO of Starseer introduces "Glass-Box Security" utilizing Mechanistic Interpretability and Latent Space Geometry to monitor model's internal state for malicious intent and data exfiltration. Perimeter defenses are failing against next-generation AI agents. Presents Starseer architecture—a technical reference for building "Internal EDR" replacing fragile regex filters with "semantic tripwires" detecting deception and code leakage at the neuron level.

Carl Hurd is Co-Founder & CTO, Starseer.

Watch on YouTube: https://www.youtube.com/watch?v=JZlaijmG-Ng

Day 1 | Stage 2

Managing Director from Consortium Networks introduces a capability-based framework for AI security. The market has 60+ vendors with unclear guidance. Framework zeros in on risks actually relevant to your architecture, helps decide how to address them (configure, buy, or build), and produces rational vendor shortlist instead of analysis paralysis. Live demo with realistic scenario: agentic healthcare chatbot with PHI data.

Maxim Kovalsky is Managing Director, AI Security CoE, Consortium Networks.

Watch on YouTube: https://www.youtube.com/watch?v=U1TJpMpxZiU

Day 1 | Stage 2

Security architect for government agencies discusses when AI leaves the screen and enters the physical world, failure shifts from misinformation to kinetic damage. Physical AI is fundamentally different: while performance dominates design, security, risk, and governance must be built in from start. Examines VLA-specific risks like sensor spoofing and embodied instruction manipulation that can lead to unsafe physical actions.

Padma Apparao is Security Architect, Government Agencies.

Watch on YouTube: https://www.youtube.com/watch?v=YzP3Fif_DHU

Day 1 | Stage 2

Agentic AI Builder from AWS presents complete open-source pipeline for trajectory-aware post-training of open-weight SLMs for cybersecurity tasks. Everyone talks about AI agents for security but almost no one discusses post-training underlying open-weight models. Frontier APIs work for prototypes but scaling autonomous security operations requires fine-tuned small language models optimized for specific tooling and reasoning patterns.

Aaron Brown is Agentic AI Builder, AWS.

Madhur Prashant is Applied AI/ML Engineer, AWS.

Watch on YouTube: https://www.youtube.com/watch?v=4zoYCfHwhEk