Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Real Risks of Agentic AI in the Enterprise with Camille Stewart-Gloster

In this episode of Data Security Decoded, host Caleb Tolin is joined by Camille Stewart-Gloster, CEO of CAS Strategies and former Deputy National Cyber Director, to unpack how AI is redefining cyber risk at every layer of the organization. Camille explains why identity-based attacks are so effective and how non-human identities (from APIs to AI agents) are quietly expanding the attack surface. She emphasized how critical MFA is for organizations to enable as they scale up AI operations, and why conditional access and governance must be foundational, not optional.

Why Your AI Agents Aren't Enterprise Ready #ai #shorts

Stop building AI agents that CISOs will never approve. If your agents are stuck in the POC (Proof of Concept) stage, it’s likely because they lack a "Passport" and a governance framework. In this clip, Arjun Subedi breaks down why "how well it works" isn't the biggest question in AI anymore—it's "how can I govern it?" Discover how mapping AGENTIC attacks to the MITRE ATT&CK framework through SafeMCP is the missing link to enterprise-level deployment.

Why reducing AI risk starts with treating agents as identities

As AI systems are used in our day-to-day operations, a central reality becomes unavoidable: AI doesn’t configure itself and must be set up with human approval and oversight. It requires engineers and developers to configure it. Developers need privileges to access and implement components, agents, tools, and features of the platforms. But developers don’t just have these privileges unconstrained… right? Where trust and privileges exist, someone will try to abuse them.

Trust in the age of AI for fintech auditors

There is an old saying: Trust, but verify. For Third-Party Risk Management auditors in regulated financial institutions, that principle has never been more relevant. Vendor questionnaires, SOC 2 reports, and annual reassessments are no longer enough. Regulators are moving beyond paper-based oversight and toward operational proof. The new expectation is clear: Show where customer data is actually flowing. Prove that you control it.

Dangling DNS in the AI Era: The Silent Attack Surface Expanding Beneath Your Feet

Artificial intelligence is accelerating digital transformation at an unprecedented pace. New AI-driven applications, copilots, data pipelines, APIs, and cloud services are spinning up faster than ever before. But while innovation moves at machine speed, governance often lags behind. The result? A rapidly expanding external attack surface filled with forgotten assets, abandoned cloud resources, and misconfigured DNS records — many of them quietly waiting to be hijacked.

Is AI dangerous?

AI is everywhere—writing emails, creating videos, even cloning voices. But artificial intelligence also comes with real risks, including privacy concerns, deepfakes, and smarter online scams. Artificial intelligence learns by spotting patterns in massive amounts of data—and that power can be misused. AI tools may collect personal information, create realistic fake content, or help scammers craft messages that look completely legit.

Can You Trust AI Code? I Built a Scanner to Find Out

Can you trust the code AI generates? In this video, we build a custom AI Security Benchmarking tool to put models like Gemini, Mistral, and GLM 4.5 to the test. Using Windsurf, OpenRouter, and Snyk, we automate a pipeline that prompts multiple LLMs to write an application, then immediately scans the output for security vulnerabilities.

Moltworker (for OpenClaw) & Markdown for Agents: Running AI on Cloudflare

Celso explains how Markdown for Agents was conceived, built, and shipped in just one week, why AI systems prefer markdown over HTML, and how converting a typical blog post from 16,000 HTML tokens to roughly 3,000 markdown tokens can reduce cost, improve speed, and increase accuracy for AI models. We also explore Moltworker, a proof-of-concept showing how a personal AI agent originally designed to run on a Mac Mini can instead run on Cloudflare’s global network using Workers, R2, Browser Rendering, AI Gateway, and Zero Trust.