Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Yes, You Need AI to Defeat AI

Long-time followers of mine know that I am not an AI hype person. Some people might even call me an AI critic. I prefer to call myself an AI realist. I do not think AI will kill us all (despite our best efforts to bypass all guardrails and common sense). I do not think AI will replace all jobs. I do not think AI will replace all cybersecurity jobs. But I do think AI allows improvements in many areas, including cyber defenses, over traditional tools and techniques.

How to migrate hundreds of Splunk SPL queries using AI

Discover how AI can convert and migrate hundreds of Splunk SPL queries efficiently while providing detailed explanations for validation. Learn how to reduce manual effort and speed up SIEM transitions. Additional Resources: About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

AI-to-AI Communication and Secret AI Code Must Be Stopped At All Costs

As I wrote in my recent book, How AI and Quantum Impacts Cyber Threats and Defenses, as we humans use AI more and more, AI will begin to communicate with itself using new AI-only communication methods that humans cannot easily see or read. If there is no human-readable audit trail or code, this is a very, very bad thing. It must be stopped at all costs. Humans are absolutely beginning to use AI more and more to do things they used to do manually. Soon, we will all be using multiple AI agents.

Best AI Intrusion Detection for Kubernetes: Top 7 Tools in 2026

Why do traditional intrusion detection systems fail in Kubernetes? Legacy IDS tools were built for static servers with fixed IPs and clear network perimeters—Kubernetes breaks all of those assumptions. Ephemeral pods, east-west traffic, encrypted service mesh communication, and dynamic IP addresses make perimeter-focused, signature-based detection effectively blind inside clusters.

Trusted AI Adoption (Part 1): Consolidation

Imagine your lead Software Engineer walks into your office and says, “Good news! I just deployed that critical update to production. I wrote the code on my personal laptop, didn’t run it through CI/CD, skipped the security scan, and just copied the files directly to the server with a USB drive.” You would fire them. Or you would revoke their access immediately.

Hackerbot-Claw Crosses the Line - The 443 Podcast - Episode 361

This week on the podcast, we chat about an OpenClaw bot that moved beyond vulnerability research and into malicious activity. Before that, we cover an AI-discovered vulnerability in the pac4j-jwt authentication library before ending with a discussion on an upcoming California law designed to help make age verification in the digital age easier, but with massive consequences.

Why AI-Native Endpoint DLP Is The Foundation of Modern Data Security

For a long time, data loss prevention (DLP) lived in the margins of security programs. It was something teams deployed to satisfy a requirement or reduce obvious risk. A handful of policies, some visibility into network traffic, maybe a scan of cloud storage. That was usually enough. That model reflected how work used to happen. Data moved more slowly, lived in fewer places, and followed more predictable paths. That is no longer true.