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Securing AI Part 2: What Makes Protecting AI a Unique Challenge?

Securing AI Part 2: What Makes Protecting AI a Unique Challenge? In part 2 of our "Securing AI" series, security experts Jamison Utter, Diptanshu Purwar, and Madhav Aggarwal discuss the unique and evolving challenges of protecting AI systems, particularly Large Language Models (LLMs). They review why traditional security methods, like firewalls and simple behavioral analysis, fall short in a world where AI is dynamic, data-driven, and unpredictable.

Seven Best Practices for Privileged Access Management

Privileged accounts are high-value targets, and without the right controls, they can become your biggest security risk. In this video, we break down seven best practices for Privileged Access Management (PAM) that help protect sensitive systems, enforce least privilege and reduce the chances of unauthorized access.

How Trust Centers and AI are replacing security questionnaires and accelerating B2B sales

As Anna say in the podcast, “Security reviews show up just when you think the deal is about to close. It’s like a final boss that no one wants to fight.” The last-mile friction caused by security diligence isn’t new, but it’s becoming more painful as deal cycles tighten and expectations around transparency rise. Buyers want answers faster. Vendors want to close faster. And security teams, stuck in the middle, are often left juggling risk, reputation, and revenue timelines.

What is Data Lineage?

In this video, we break down the concept of data lineage — a way to track how data moves, changes, and is used across your organization. Data lineage provides visibility into the lifecycle of sensitive information, from where it originates to where it flows, and who interacts with it. Understanding data lineage helps organizations improve security, ensure compliance, and reduce insider risk. Watch now to learn what data lineage is, why it matters, and how it helps protect your most valuable data.

What is Insider Risk Management?

In this video, we explain the basics of insider risk management — the practice of identifying, assessing, and reducing the risks that come from employees, contractors, or partners who have access to sensitive data. Insider risk management goes beyond traditional data loss prevention by addressing both malicious and accidental insider threats. From protecting intellectual property to preventing data leaks, insider risk management helps organizations secure their most valuable information.