Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

armo

AI Agent Sandboxing for Healthcare: Why Standard Kubernetes Primitives Can't Express HIPAA Boundaries

Apr 30, 2026 By Yossi Ben Naim In ARMO
Observe-to-enforce builds behavioral baselines from observed agent traffic — what tools the agent calls, which networks it reaches, which syscalls it executes — and converts them into per-agent enforcement policies. Baselines persist at the Deployment level because pods churn and the envelope has to outlive any single restart. The methodology runs as a four-stage progression: discovery, observation, selective enforcement, continuous least privilege.
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LimaCharlie

Agentic AI Security: Tune Detections with Threat Intel

Apr 30, 2026 By Daniel Ballmer In LimaCharlie
Most AI detection engineering puts a human in the loop at every step. David Burkett envisions an efficient and effective pipeline architecture that does not. David is a security researcher at Corelight Labs and a longtime LimaCharlie community member. He appeared on a recent episode of Defender Fridays to walk through his vision of a fully agentic detection engineering pipeline. His system uses LimaCharlie as its operational backbone.
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This AI Safety Move Makes Zero Sense #aisafety #ai #tech

Apr 30, 2026 By Razorthorn Security In Razorthorn
Claiming an AI model is too dangerous for public release while issuing a press release about it creates more questions than trust. If something genuinely carries that level of risk, private handling under strict controls makes sense, but public hype only fuels suspicion, competition and panic.
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armo

AI-SPM for Financial Services: Managing AI Risk Under SOC2, PCI-DSS, and MAS TRM

Apr 29, 2026 By Shauli Rozen In ARMO
The external auditor’s evidence request lands Tuesday morning. A security architect at a Tier 1 bank pulls up her AI-SPM dashboard for the SOC2 Type 2 review. Eighty-three AI agents running across the bank’s clusters. For each one, the dashboard shows the current configuration and the current behavioral baseline. The data is accurate, comprehensive, and point-in-time.
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armo

Prompt and Tool Call Visibility: What Your AI Agents Are Actually Doing

Apr 29, 2026 By Yossi Ben Naim In ARMO
It is 11:47 p.m. and the on-call security engineer is staring at two dashboards. On the left, LangSmith — the ML team’s debugging stack — showing the agent’s prompts, model responses, tool calls, and tokens consumed. On the right, the runtime detection console showing eBPF-captured syscalls, network connections, and process trees from the same Pod. Both are populated.
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elastic

Whole-of-state cyber defense: How AI-driven security helps US states protect what matters most

Apr 29, 2026 By Bobby Suber In Elastic
Short answer: Because attackers exploit fragmentation faster than governments can respond This shift toward collective cyber defense is a cornerstone of the new federal vision. The March 2026 National Cyber Strategy for America explicitly calls for a "new level of relationship between the public and private sectors" and demands "unprecedented coordination across government" to protect the American people.
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Datadog MCP Server, Experiments, Bits AI Security Analyst, and more | This Month in Datadog

Apr 29, 2026 By Datadog In Datadog
April’s This Month in Datadog spotlights the Datadog MCP Server, which gives AI agents secure, real-time access to Datadog telemetry, and Datadog Experiments, which lets you design, launch, and analyze experiments to see the full impact of product changes on the user journey. Plus, we cover how to: Accelerate Cloud SIEM investigations with Bits AI Security Analyst Remediate vulnerabilities in your codebase with Bits AI Dev Agent for Code Security Explore Datadog with natural language using Bits Assistant.
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