Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The AI arms race in deepfake detection has a critical problem: the technology can't keep up. In this episode, Navroop Mitter, CEO of ArmorText, discusses why the industry is shifting away from relying on AI detection alone. A recent study from SKKU in South Korea found that zero out of sixteen top deepfake detection technologies could reliably identify deepfakes in real-world conditions. They worked fine in controlled lab settings, but failed when it mattered most.

AI agents now move data, collaborate, and make decisions at machine speed — millions of actions per second. But our entire security architecture was built for humans, not for autonomous AI. In this new Agentic World, every action is faster, every breach more invisible, and every compliance gap more dangerous. Protecto introduces Agentic Controls — intelligent, context-aware CBAC Agents that live inside AI workflows. They understand policies written in plain English, enforce zero-trust decisions before data ever leaves its boundary, and protect privacy across industries.

CISOs aren’t losing sleep over zero-days. The real threat? Their own employees. From phishing to prompt injection, discover what keeps security leaders up at night.

AI is changing everything—but with innovation comes new risks. In this episode of AI on the Edge, we dive deep into OWASP's Top 10 for Large Language Models with security leader Steve Wilson (Exabeam). Discover why every tech company is suddenly talking about LLM security and how you can stay ahead. Inside this episode: Why traditional security doesn’t work for AI Learn from Steve’s new book The Developer’s Playbook for LLM Security and get actionable tips to protect your AI systems.

From Model Drift to API Exploitation: The Next Challenge in AI Security In this clip from "Securing AI Part 4: The Rising Threat of Hidden Attacks in Multimodal AI," Diptanshu Purwar and Madhav Aggarwal summarize why external guardrails are the only sustainable defense against the new wave of AI exploitation. Jamison Utter then sets the stage for the next topic in the series: securing the fundamental protocols and APIs that AI agents rely on.

From identification to remediation to drift management. When Reach flags an exposure, it doesn’t stop there. It shows exactly how much risk you’ll reduce by fixing it — and what impact it’ll have on users. In this short demo, CRO Jared Phipps walks through how Reach:︎ Quantifies residual risk reduction (e.g., 62%, 91%, etc.)︎ Weighs that against user impact︎ Guides teams through the remediation process︎ Integrates with Jira or other ticketing systems to track fixes︎ Monitors configurations to prevent drift and maintain baselines.