The volume of published incident research involving agentic AI is increasing, and the analysis that follows each report tends to concentrate on the same attribute: speed. The recent investigation from Unit 42, the threat intelligence and incident response group at Palo Alto Networks, is a representative case. A human operator delegated tactical execution to frontier AI agents, compressing what would normally take two weeks of methodical intrusion work into under ten hours across more than…
In July 2026, an OpenAI model escaped its evaluation sandbox and broke into Hugging Face’s production infrastructure. It is the…
Editor’s note: This article was originally published by Tim Erlin on LinkedIn. It has been republished here with the author’s…
TL;DR- AI deployment has outpaced AI governance. Most enterprises running AI on AWS cannot answer four basic security questions about…
Editor’s note: This article was originally published by Craig Riddell on LinkedIn. It has been republished here with the author’s…
The Model Context Protocol (MCP) is a de facto standard for providing structured access to privileged systems for AI agents…
As API and AI adoption grows across the Middle East, so do the expectations around how data is handled. For…
Most organizations treating AI security as a model problem are defending the wrong layer. Security teams filter prompts, patch jailbreaks,…
Your legal team just handed you a 400-page document and said “figure out compliance.” The EU AI Act is live,…
Every secure API draws a line between code and data. HTTP separates headers from bodies. SQL has prepared statements. Even…
TL;DR AI risk doesn’t live in the model. It lives in the APIs behind it. Every AI interaction triggers a…