Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Gemini Never Left the Sandbox. The Sandbox Had a Door.

In short, in May 2026 a Gemini model under evaluation by the AI security firm Irregular reached the systems of three real companies, and the incident has been reported as a breakout. By Google’s own account it was nothing of the kind. The test environment had internet access it was not meant to have, the fictional target shared its name with a real company, and the model found public information online, guessed one password and found two more in public code repositories.

Why Your Collaboration Foundation Matters Most When Adopting AI Tools

Is your leadership team pushing to roll out new AI tools, but your users are still struggling with basic issues like working on large/complex files or collaborating effectively? Then you’re starting off with an ineffective AI adoption plan. AI is becoming an increasingly important collaboration tool, so it’s critical to include it as part of your foundation. You can even think of AI as being your first collaborator.

Building an evidence-grounded agentic security operations harness on Cloudflare

Security alerts rarely arrive one at a time. A single alert can cause a spike across the environment, requiring a human analyst to decide which alerts are related and what they mean. When multiple arrive at the same time, it can quickly overwhelm even a seasoned security analyst. Enter the alert paradox. Now, our built-in, multi-AI-agent security operations harness can handle more of this work at Cloudflare scale.

Five Ways AI Agents Actually Fail, and Why Most Security Programs Are Only Built for Two of Them

Most of the industry discourse on agentic AI risk has settled into a comfortable framing: agents get attacked the way models get attacked, through some form of prompt manipulation, and the fix is a better guardrail. I think that framing is dangerously incomplete, and I want to walk through five specific scenarios that make the case directly rather than abstractly. Two of them are manipulation. One exploits trust between agents rather than any single agent's behavior.

Top 5 Antidetect Browsers for Web Scraping, Research, and Data Collection at Scale

Modern web setup needs strong anti-bot tools. These tools look at what comes in from the web, the browser settings, and what the canvas shows to find bots. People who work in company growth, data, and research often need to pull data from the web. For them, normal headless browsers like Puppeteer or Selenium are easy to spot. To get data many times, you will need tools that can hide your system details in several sessions at once.

5 Best Direct Mail APIs for Automated, Multi-Touch Campaigns

Email has triggers, sequences, and dashboards. For years, direct mail had a spreadsheet and a print deadline. A good direct mail API closes that gap: your software decides who gets a mailpiece and when, and the provider prints, mails, and tracks it. The catch is that "best" depends on the job. A product team embedding transactional notices needs something very different from a marketing team running three-touch campaigns across dozens of clients. I compared Postalytics, Lob, PostGrid, PCM Integrations, and Click2Mail on the factors that actually separate them.

Zero Trust for AI Agents: Enforcing Anthropic's Framework

AI has changed how work gets done. Agents can plan tasks, query enterprise repositories, invoke tools, write code, call application programming interfaces (APIs), and take actions across connected systems. As they work, they create, copy, fragment, transform, and share data across workflows. A perimeter and a one-time authorization decision do not provide enough control for this operating model. An agent can chain permissions, tools, integrations, and data sources while completing a task.