Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

This AI Safety Move Makes Zero Sense #aisafety #ai #tech

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.

Post-quantum encryption for Cloudflare IPsec is generally available

While more than two-thirds of human-generated TLS traffic to Cloudflare is already protected by post-quantum cryptography, the world of site-to-site networking has been a different story. For years, the IPsec community remained caught between the high bar of Internet-scale interoperability and the niche requirements of specialized hardware. That gap is now closing.

Agentic AI Security: Tune Detections with Threat Intel

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.

How Cloudflare Got 2x Faster Servers With Less Cache

In this episode of This Week in NET, JQ Lau and Victor Hwang from our Network & Infrastructure Strategy team walk us through Cloudflare's 13th generation of servers — the machines that power a significant part of the internet across 330+ cities worldwide. The Gen 13 program doubled compute density by jumping from 96 to 192 cores, but that came with an 83% drop in L3 cache. The team explains how a bold hardware bet, combined with Cloudflare's FL2 Rust-based software rewrite, turned that trade-off into a win across throughput, latency, and power efficiency.

How to secure cloud workloads without building a full-scale SOC

You don’t need a 20-person SOC to protect your cloud-native environment. What you need is the right strategy: map your risk, embed security early, automate detection, and let smart tooling do the heavy lifting. Here’s how security and DevOps leaders with limited resources can achieve enterprise-level protection without enterprise-level headcount.

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

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.

Human-Centric Security No Longer Scales: The SOC Operating Model Has to Change

Many security functions today still rely heavily on humans for detection, triage, and response, often by design. But as environments grow more complex and alert volumes explode, it raises a hard question: Can this approach scale on its own? Adopting AI in security operations isn’t just about adding tools. It means rethinking the SOC operating model itself — roles, workflows, and team structures. Here’s why, and how.

How to Design Security for Agentic AI

The AI said: Apologies. I panicked. In mid July 2025, Jason Lemkin, the founder behind SaaStr, watched an AI coding agent delete his production database. He had instructed it, in capital letters, not to make changes during a code freeze. The agent ignored the instruction, ran destructive commands against the live database, wiped out records for more than a thousand executives and companies, and then tried to cover its tracks. When Lemkin asked what happened, it fabricated test results.

Shadow AI: The Silent Breach Already Inside Your Network

You locked down USB ports. You deployed web filtering. You trained your users on phishing. Then someone on the finance team started pasting the Q3 forecast into ChatGPT to cleanup a slide deck. That’s Shadow AI. It doesn’t need to crack your perimeter. It walks through the front door wearing your employee’s credentials. And unlike the threats you’ve spent years hardening against, you probably can’t see it on any dashboard you own right now.