Insider Risk National Symposium 2026
September 15–16, 2026
Washington, D.C.
Thank you for attending the Insider Risk Symposium &
US COE, Insider Risk Boot Camp
Below are materials from the sessions and related handouts presented by
Frank L. Greitzer, PhD, Chief Scientist at Cogility.
PRESENTATION (DSI)
AI Agents as Digital Insiders: A New Frontier for Insider Risk Management
As AI agents become embedded in enterprise and mission systems, they introduce a new class of insider risk that traditional security tools are not designed to manage. This talk will argue that effective AI governance must address the full "human-agent-system" triad. The presentation outlines a practical path toward scalable, explainable governance for agentic AI as organizations confront this rapidly emerging security challenge.
PRESENTATION (BOOT CAMP 9/17)
Agentic AI: An Emerging Threat Vector
As AI agents move from copilots to autonomous actors, they create a new class of insider risk that traditional security and HR frameworks weren't built to catch. This session, presented by Frank Greitzer, Chief Scientist at Cogility Software, extends SOFIT—an established insider-risk framework—into SOFIT-AI, feeding Cogynt.ai's Agentic Security architecture. Using Hierarchical Complex Event Processing, a real-time Edge checkpoint and deeper Enterprise Analytics layer fuse human and agent signals into deterministic, auditable alerts before risk becomes breach.
FACT SHEET
Runtime Protection for Enterprise AI Agents
Cogility Agentic Security & Behavioral Enforcement Solution
Agentic AI is a new class of digital insider. This document describes the technical approach and system architecture of Cogility’s Agentic Security and Behavioral Enforcement solution that extends two decades of insider-risk taxonomy to agentic systems. Cogynt.ai pairs two decision systems—the Edge component performs deterministic policy checks in sub-millisecond time to decide whether to forward, redact, block, or escalate; the Enterprise component runs continuously in the background, correlating activity across sessions and actors to turn raw telemetry into composite patterns to support systemic risk judgments.
More Insider Risk Resources
Discover more about our solution and Cogynt.ai. Below are materials from previous events that can help you stay informed on the latest advancements in insider risk management and to learn more about Cogility.
Insider Risk Management Materials
DATASHEET
Insider Risk Management
Insider risk remains one of the most damaging threats an organization can face. Yet many programs still depend almost entirely on catching explicit violations and anomalies after they happen. Security teams are left racing to identify and respond to policy breaches, unusual user activity, and malicious behavior spread across scattered locations, devices, and systems.
VIDEO PRESENTATION
Proactive Insider Threat Mitigation: Exploring Predictive Threat Assessments
This video discusses technical challenges and recent insights in developing and testing behavioral science-based models for proactive insider threat mitigation. Dr. Greitzer describes the SOFIT insider threat indicator ontology, which provides a foundation for hierarchical, pattern-based models; reviews what expert knowledge elicitation studies have revealed about dynamic properties of potential risk indicators; and discusses recent approaches for developing and testing models that reflect how human experts think about and analyze this complex threat assessment problem.
Insider Risk Report - Research by Cybersecurity Insiders
A 2025 survey of 635 CISOs conducted by Cybersecurity Insiders found a clear disconnect: organizations know insider risk is a growing concern, but most lack the tools and processes to get ahead of it. The findings make a strong case for a different approach — one built on predictive, whole-person intelligence rather than after-the-fact monitoring. Read the report now to see the full findings.
Case Study: 2022 Walmart Shooting Risk Assessment
This case study reveals how the 2022 Chesapeake Walmart shooting was preceded by a documented pattern of escalating warning behaviors—paranoid conduct, threats, harassment complaints—that employer records had already captured. Mapped against SOFIT Potential Risk Indicators, the pattern shows how isolated incidents can compound into extreme risk. Cogynt.ai's retrospective analysis, using only pre-attack data, flagged both violence and self-harm risk at critical levels—raising the question of what proactive detection could have changed.
Decision Intelligence Platform
DATASHEET
Cogynt.ai - A Decision Intelligence Platform
Enterprise and government adoption of big data and streaming technologies calls for a new class of decision intelligence (DI) applications to support critical decisions. DI applications strengthen situational awareness, improve operational efficiency, and optimize risk management. Building DI capability with fragmented tools drives up development and resource costs. Organizations need a scalable, integrated decision intelligence platform (DIP) that simplifies management and speeds delivery — improving predictive analysis and making better use of analyst, data science, and engineering resources.
SOLUTION BRIEF
Cogynt.ai – a Continuous Decision Intelligence Platform
Many companies face data volumes that outpace traditional analytics, leaving them reactive rather than proactive in critical decision-making. Current solutions struggle to deliver comprehensive risk assessment and opportunity identification in complex environments.
Cogility has spent more than 10 years developing Cogynt.ai, a decision intelligence platform (DIP) that delivers continuous intelligence through Expert AI behavioral analytics, processes large data streams into actionable situational awareness, and provides auditable insights answering "why" behind critical decisions. Read the solution brief now.
WHITE PAPER
Behavioral Analytic Platform: ROI Projection for Cogynt.ai
This paper develops a business case for Cogynt.ai, a high-fidelity/high-automation Behavioral Analytic Platform, contrasting it with traditional, lower-fidelity/low-automation approaches for Insider Risk Management (IRM). To inform prospective adopters of this technology, the analysis focuses on projecting the Return on Investment (ROI) and risk reduction benefits for a typical large organization with 100,000 personnel.
Learn More
The buttons below will help you navigate to various resources and presentations on related topics that are available in the Cogility Resource Center, blog articles, and training videos.
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Cogynt.ai provides a fundamentally different approach to detecting and countering insider threat risk. Other solutions primarily rely on user activity monitoring, which only provides half of the picture since this approach discovers technical indicators of risk only. Cogynt.ai by contrast takes a whole-person approach to detecting risks by ingesting both technical and social indicators of risk, mapping and weighting these risk indicators to behaviors, and creating a whole-person profile.
By taking this approach, Cogynt.ai allows organizations to have a more accurate and holistic picture of insider threat risks - providing a window of opportunity to get left of harm.
Please contact us if you’re interested in piloting Cogynt.ai.