Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Firewalls are the single most common source of misconfiguration-related breaches, yet they get changed a hundred times a week and audited once a quarter. This is the network security gap AI attackers exploit first. Endpoint gets the budget. Identity gets the roadmap. The firewall gets changed constantly and reviewed rarely. It is also the control most tied to breaches: 42% of security teams pinned a firewall misconfiguration to a breach or near miss last year, ahead of EDR at 40% and identity at 39%.

Sensitive data used to live in predictable places database columns, known field names, structured rows. That changed when data moved into documents. And it changed again when AI workflows arrived. In this video, we walk through why detecting sensitive data in AI pipelines is fundamentally different from traditional data discovery, and why the old approaches break. We cover the four failure modes that make detection hard in AI workflows.

AI Is Accelerating the Cyber Kill Chain: Faster Attacks, Greater Risk AI is changing the speed and scale of modern cyber attacks. From accelerating reconnaissance to reducing the time required for initial access, attackers are leveraging AI to move faster across the entire cyber kill chain. In this video, Paul Girardi explains how AI is impacting each stage of the attack lifecycle, including: As attackers automate more of the kill chain, security teams need smarter approaches to detect, disrupt, and deceive adversaries before they can achieve their objectives.

As organizations adopt agentic AI, we believe open collaboration is the fastest path to building trustworthy AI governance. Today, we're introducing a new open source project: Agentic Trust Controls. Agentic Trust Controls are designed to help the GRC community evaluate and govern AI agents with greater consistency and confidence. Explore the project and share your feedback at trustcontrols.ai.