Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Security awareness programs are built on measurement. Before you can reduce human risk, you need a clear understanding of where knowledge gaps exist across your workforce. For many organizations, that process starts with a baseline assessment. For years, KnowBe4’s Security Awareness Proficiency Assessment (SAPA) has provided that foundation.

Enterprise DLP solutions in 2026 must cover far more than email and USB channels. With many employees pasting data into GenAI prompts and sensitive data flowing across cloud, SaaS, and browser-based AI tools, legacy DLP architectures leave critical gaps. Choosing the right platform requires mapping where sensitive data lives, identifying real exfiltration paths, and deciding whether a standalone, native, or converged DSPM-plus-DLP architecture fits your environment.

You have six ways to send a large amount of photos:cloud storage links, dedicated file transfer tools, email with a workaround, messaging apps, device-to-device transfer, and physical drives. Which one works best depends on how many photos you're sending, whether quality matters, and how private you need it to be. The default options most people try first all have real limits. Email cuts off around 25MB, which is about 5 to 10 full-quality photos.

For many organizations, a single security lapse isn’t just a technical glitch — it’s a catastrophic blow to their brand reputation and bottom line. With the global average cost of a leak reaching record highs ($4.44 million according to 2025 estimates), learning how to prevent data theft has shifted from a best practice to a business necessity. But how do you stay ahead of the latest cyber threats?

As endpoints became more powerful, more mobile, and more exposed, they also became more prone to attacks. Endpoints remain one of the most targeted entry points for attacks. Attacks today are no longer random; they are targeted, deliberate, and increasingly powered by automated AI discovery tools that hunt for unmanaged gaps. Malware, ransomware, and phishing-based intrusions continue to increase, and their first level of interaction often happens on an endpoint.

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.

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.

Cyber protection, management and automation of IT deployments is fundamentally an exercise in responsibility and trust. That is especially true in the age of AI, where innovation moves fast and the consequences of failure can be severe. Organizations today need confidence that their IT providers are not only technically capable, but also reliable, transparent and accountable. Entrusting a partner with your infrastructure is the ultimate trust exercise.

Zero trust used to sound like yet another security buzzword. In SaaS environments, it has turned into something far more practical: a way to keep your business moving fast without assuming that anything or anyone is safe just because they are “inside” your systems. Zero trust in SaaS is about treating every login, every device, and every request as something you verify in real time instead of something you blindly trust because it passed a VPN check once.

Production deployments. That’s where multi-agent AI systems live now, not research labs. Salesforce, Microsoft, and Cognition Labs are all running agent pipelines that replaced what used to take entire ops teams. Most businesses still don’t fully understand what they’ve switched on. A multi-agent AI setup isn’t just one model doing more things.