Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In its January 2026 report, Emerging Tech: Tech Innovators in Domain-Specific Language Models for SecOps, Gartner examines how domain-specific language models (DSLMs) are reshaping security operations. The report explains that DSLMs are designed to address the limitations of general-purpose language models by focusing on a particular task or use case – in this case, cybersecurity.

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.

CrowdStrike Falcon for XIoT is extending its industry-leading protections to medical devices in healthcare environments. This will provide comprehensive security for patient care at a time when healthcare organizations are a key target for threat actors. As of January 2026, the HHS listed over 750 reported breaches within healthcare environments that were under investigation.

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.

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.

Why do traditional incident response playbooks break in Kubernetes? Pods spin up and disappear in seconds, destroying forensic evidence before you can investigate. Attackers exploit service account tokens and move laterally through east-west traffic that perimeter tools never see—over 50% of ransomware deploys within 24 hours of initial access, leaving no time for manual investigation methods built for static servers.

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.

AI pentesting has been making waves and rivals the power of human hackers in ways we weren’t expecting. But frequently, companies are looking for pentesting to achieve and support their compliance certifications.

Read the takeaways from ConFoo 2026, including putting guardrails where requests happen, auditing tool calls, treat dependency updates like production access.