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.

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.

Most ATO detection tools are watching the wrong moment. Attackers don’t start at your login page – they start days earlier, registering lookalike domains, cloning your site, and harvesting credentials before your stack sees a single signal. Knowing how to detect account takeover means moving detection upstream: to the reconnaissance stage, the cloning event, and the live harvesting window. That’s where the attack is stoppable.

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

It’s impossible to walk into a tradeshow these days without getting blasted by a wall of acronyms. Everywhere you look, vendors are cramming two to four perfectly serviceable words into a string of capital letters arranged to sound cooler than they actually are. This wouldn’t be so bad if it didn’t routinely derail meetings, product decisions, and sometimes whole strategies.

For many organizations, Grafana is a central operational system. Engineers use it to investigate issues, analyze logs, review infrastructure metrics, and query production-connected databases. But while dashboards are visible, the real sensitivity lies in the underlying data sources Grafana connects to. These data sources often include systems such as logs stored in Elasticsearch or OpenSearch, SQL databases like PostgreSQL or MySQL, and Amazon CloudWatch metrics.

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.