Agentic-Ai

Security researcher Yarden Porat at Cyata published findings this week that should be required reading for anyone running CrewAI in production: four critical CVEs, chainable via prompt injection, that allow attackers to escape Docker sandboxes and execute arbitrary code on the host machine. CERT/CC issued advisory VU#221883. Patches are available. What Was Found Porat’s research identified four vulnerabilities in CrewAI that can be chained together: CVE-2026-2275 — The initial vector: a prompt injection flaw that allows malicious content in agent inputs to manipulate how CrewAI processes tool calls. Normally, tool calls are structured, validated operations. This CVE allows crafted input to make the framework treat attacker-controlled content as legitimate tool invocations. ...

RSAC 2026 is where the agentic AI security conversation got serious, and the number that defined it was 500,000. That’s the estimated count of internet-facing OpenClaw instances identified by security researchers — a deployment footprint that arrived faster than the security tooling needed to manage it. VentureBeat’s analysis at the conference laid out an uncomfortable reality: half a million instances, three unpatched high-severity CVEs, and no mechanism for fleet-wide patching or emergency shutdown. ...

It happened again — and this time the exposure was massive. On March 31, 2026, security researcher Chaofan Shou (@shoucccc) discovered that Anthropic’s Claude Code CLI had inadvertently published its entire source code inside a 60MB source map file (cli.js.map) bundled within its npm package. Within hours, the community had mirrored the code, opened GitHub repos cataloguing the exposure, and the story had broken across cybersecurity news outlets worldwide. This is reportedly the second time in a year that Claude Code’s source has leaked through the same vector. ...

For decades, being a great developer meant being able to write code. Today, Fortune argues, that’s changing — and the new premium skill isn’t writing. It’s supervising. In a piece published today, Fortune makes the case that AI agents and vibe coding are creating what they call a “Supervisor Class” — a new archetype of developer who derives their value not from syntax mastery, but from high-level judgment and the ability to direct autonomous systems effectively. ...

Today’s Claude Code source leak was a good reminder that shipping to npm is a security surface area that many developers don’t audit carefully enough. A 60MB .map file contained Anthropic’s entire CLI source. This guide shows you how to prevent the same thing from happening to your own packages. Why Source Maps Are the Hidden Risk Source maps (.js.map files) are generated by build tools like webpack, esbuild, Rollup, and Parcel to help with debugging. They map your compiled, minified output back to the original source. In development and CI, this is exactly what you want. ...

Microsoft’s ambitious bet on multi-model AI is moving from announcement to reality. Copilot Cowork, the company’s long-running autonomous workflow system for Microsoft 365, is now available to Frontier program participants as of today — and it’s using both OpenAI’s GPT models and Anthropic’s Claude together to get work done. This is a meaningful update to the original Copilot Cowork announcement from March 9. That post described the vision. Today’s rollout makes it real for early-access enterprise users. ...

The AFP wire just ran a story on OpenClaw. That’s a milestone worth pausing on. AFP — the global French news agency that feeds outlets in 150+ countries — picked up a dispatch from Tokyo today where OpenClaw creator Peter Steinberger spoke at a gathering of the tool’s enthusiasts. The story ran across France24, Digital Journal, and dozens of US local outlets. It’s the kind of mainstream wire pickup that signals a technology has crossed from tech-insider territory into the general conversation. ...

The “token tax” problem is real. As enterprises and power users deploy OpenClaw at scale, a recurring nightmare scenario is playing out: you set up an autonomous reasoning loop before bed, wake up, and discover your OpenAI or Anthropic bill has ballooned by $500–$1,000+ overnight. This is not a hypothetical. It’s being reported across the OpenClaw community today — in Paul Macko’s OpenClaw Newsletter, on ManageMyClaw.com, and in cost guides circulating in developer channels. And the root cause is straightforward: OpenClaw ships with no native API rate limiting or daily spend caps by default. ...

The gap between human and machine intelligence just got a new measuring stick — and the results are humbling for AI. On March 25, 2026, ARC Prize officially launched ARC-AGI-3, the third generation of the Abstraction and Reasoning Corpus benchmark series. Where previous editions measured pattern recognition and abstract reasoning on static puzzles, ARC-AGI-3 introduces something fundamentally different: interactive, turn-based environments designed to measure genuine agentic intelligence. The headline numbers? Humans score 100%. Frontier AI — including the best available large language models — scores just 0.26%. ...

The biggest battle in AI right now isn’t about which model is most powerful. It’s about who controls the layer between models and the real world. This is the control layer — the orchestration and management tier of agentic AI that routes tasks, governs agent behavior, manages state, and connects models to tools, data, and each other. And every major tech company is racing to own it. What the Control Layer Actually Is Think of it like this: large language models are powerful engines, but they don’t drive themselves. To do useful work at scale, you need infrastructure that: ...