Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

We are witnessing the birth of a new profession in the blend of security engineering and security operations, a discipline that didn't exist five years ago because the systems it protects didn't exist five years ago. As artificial intelligence moves from experimental to essential and agentic systems begin to perceive, reason, act, and learn autonomously, we need defenders who can operate at the same velocity. I'm talking about the AI Security Engineer.

Financial services organizations moving to AWS often discover that retrofitting security and compliance controls costs three to five times more than building them in from the start. Compliance gaps discovered during audits can delay critical initiatives, trigger regulatory scrutiny, and expose organizations to unnecessary risk.

Update (February 24, 2026): @vmfunc has published part two of their series about Persona. You can read it here. We will update this post with part three when it is released. On February 16, 2026, security researchers @vmfunc, @MDLcsgo, and @DziurwaF published a blog post identifying exposed frontend source maps on a non-production subdomain under withpersona-gov.com.

So your team just uncovered a GDPR tracking violation, a consent anomaly that, after a deeper look, turns out to be a pixel firing regardless of consent state.” From the looks of it, it’s definitely an ePrivacy violation. But the harder question, the one you now have to race against time to answer, is whether this is also a notifiable breach under GDPR. For that determination, you now have 72 hours. One gets fixed with a tag manager update and a stern email to marketing.

Most websites host tracking systems that change continuously, tag by tag, pixel by pixel, version to version, often without anyone in privacy touching a line of code. Marketing adds a session replay script through the tag manager. Vendors quietly push updates to the tags. By the time it’s noticed in the next periodic review, the damage is done. Drift in tag behaviour leads to consent violations. And tracking scripts load and process data despite GCP signals.

Picture this: it’s 2am, your pager goes off, and you’re staring at a production database that’s on fire. You know exactly what’s wrong. You know exactly how to fix it. But you can’t touch anything because you’re waiting on someone to approve your access request. Meanwhile, your customers are down, your SLAs are bleeding out, and you’re refreshing Slack, and every minute you spend waiting is another minute of damage you could’ve prevented.

Sr. Technical Content Strategist Hockey has a saying that describes the problem security organizations face when trying to integrate AI:"You have to skate to where the puck is going, not where it has been". Think of the modern security stack. It's a fragmented architecture built layer by layer over decades. Tools are siloed, some overlapping, some operating in black boxes, and others that no one remembers installing.

Teams, friends and family members often need to share access to accounts, but traditional methods like email, text messages or screenshots expose sensitive information and create lasting risk. Keeper’s One-Time Share works by creating a secure, device-bound link that allows temporary access to a record while keeping credentials encrypted and fully protected. This approach enables fast, secure sharing without requiring the recipient to create a Keeper account or gain ongoing access to your vault.

During a recent video interview, we spent time unpacking a deceptively simple question: what actually makes a vulnerability critical? Severity scores, exploitability, and asset importance all factor into the answer. But one layer of context consistently changes the urgency of a finding more than most teams expect: internet exposure. The difference between a vulnerability that exists and one that matters often comes down to whether an attacker can reach it.

Why do most Kubernetes security tools fail teams in practice? Because they treat deployment and security as separate problems. A true Kubernetes security deployment service embeds scanning, policy enforcement, and runtime monitoring directly into the deployment flow — so risky workloads never reach production in the first place. Why isn’t shift-left security enough on its own?