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By Shauli Rozen
It usually starts the same way. The CISO comes back from a board meeting having signed off on agentic AI for production. The SOC lead is told, in roughly that many words, to build detection for the agents. And the security stack she has — CNAPP for posture, EDR on the nodes, container runtime sensors, a SIEM ingesting everything — was architected before AI agents existed as a workload class.
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By Yossi Ben Naim
A platform team finishes a two-week observation window on a new internal research agent. The baseline is stable; the sensor produced a clean profile. By Friday, no policy has shipped — and the blocker isn’t tooling.
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By Yossi Ben Naim
The residency evidence GDPR and the EU AI Act now expect lives in the runtime trajectory of every AI agent execution, not in the deployment configuration. Your residency compliance dashboard — every workload in eu-west-3, sovereign cloud configured, SCCs signed — cannot produce it. Your AI agent’s last thousand inferences crossed an external border, on average, eight times each. The translation API routed through us-east-1 when the EU endpoint hit capacity.
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By Ben Hirschberg
Editing IAM policies cannot fix the most common architectural mistake in shipping AI agents on Kubernetes. It happens in thirty seconds: a platform engineer reuses an existing ServiceAccount with an IRSA annotation for Bedrock access because creating a new one takes thirty minutes plus a Terraform pull request. The new agent ships under the existing identity.
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By Shauli Rozen
Your risk committee meets Thursday. The agenda has a new item: AI agent risk posture. You open the register. The fraud detection agent shipped in March is on it. So is the customer service agent. Neither row is useful — “likelihood: medium, impact: high, control: service account scoped via IAM.” Three months ago that was approximately right. Last week the platform team added two MCP connections, the model was upgraded, and the agent now touches data classes the entry never anticipated.
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By Shauli Rozen
Most “hardening” advice for AI agents is a checklist of things to configure before the agent runs. CIS Kubernetes Benchmark gates. Pod Security Standards baselines. NetworkPolicy templates. None of it’s wrong — it’s just one of four phases, the one your stack already covers. The other three are Observe, Enforce, and Reconcile. They’re where AI agents actually get breached, and they’re where most stacks have nothing.
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By Ben Hirschberg
Every AI workload security PoC reaches the same conversation. Platform engineering pushes back: the AI team won’t accept extra latency on inference. The security engineer hunts for benchmarks and finds a contradiction. Langfuse publishes 15% overhead. AgentOps publishes 12%. The security vendor quotes 1–2.5%. None is lying. They measure different layers.
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By Shauli Rozen
It’s 2 a.m. and the SOC has a Tier 3 page. A customer-service agent on the production cluster has just wired refund payments to seven addresses outside the approved disbursement list. The runbook is unambiguous: isolate the pod, image the disk, image the memory, root-cause within 48 hours.
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By Shauli Rozen
For six weeks, a mid-size hospital system’s CDS agent issued recommendations biased by a poisoned guideline summary. No detection alert fired. The drift — denial recommendations in cases sharing one specific clinical attribute — traced back to a guideline an outside contributor had quietly reweighted in editorial review. Every existing detection stack reported green. DLP: no PHI left the cluster. EHR audit log: agent reading and writing within scope. Network egress: normal traffic.
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By Ben Hirschberg
A healthcare CISO opens her AI-SPM dashboard at the start of the quarter. Every clinical AI agent in the cluster reads green: full AI-BOM coverage, every permission scope reconciled, the HIPAA compliance tag clean across the fleet. The ambient scribe, the prior-authorization assistant, the oncology decision support agent — all monitored, all green, all the way through. Six months later, the Office for Civil Rights opens an investigation.
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By ITProTV
With the short week for the Thanksgiving holiday in the US, the Technado team decided to have a little fun by looking back at some of the dumbest tech headlines from 2019. Romanian witches online, flat-earthers, and fake food for virtual dogs - what a time to be alive. Then, Shauli Rozen joined all the way from Israel to talk about a zero-trust environment in DevOps. IT skills & certification training that’s effective & engaging. Binge-worthy learning for IT teams & individuals with 4000+ hours of on-demand video courses led by top-rated trainers. New content added daily.
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ARMO closes the gap between development and security, giving development, DevOps, and DevSecOps the flexibility and ease to ensure high grade security and data protection no matter the environment – cloud native, hybrid, or legacy.
ARMO is driving a paradigm shift in the way companies protect their cloud native and hybrid environments. We help companies move from a “close-the-hole-in-the-bucket” model, installing firewalls, defining access control lists, etc. to a streamlined DevOps- and DevSecOps led model in which environments are deployed with inherent zero-trust.
Security at the Speed of DevOps:
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