Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In the pharma and biotech sectors, a single data leak doesn’t just trigger regulatory fines. It can wipe out a decade of R&D, hand patented drug formulations to competitors, and instantly derail a clinical trial. Your most valuable assets no longer live safely inside a single corporate network. They constantly move through a fast-paced ecosystem of remote researchers, external laboratories, and Contract Research Organizations (CROs).

Attackers are using a fake Codex download experience to trick macOS users into pasting a malicious command into Terminal. This technique, known as ClickFix, relies on social engineering rather than a conventional malware download: the victim is persuaded to perform the execution step themselves. We analyzed sponsored search results leading to convincing Google Sites pages, a no-code website-building and hosting service provided by Google.

There is a public record of every TLS certificate ever issued for your domain, and anyone can search it. Most people who run infrastructure have never heard of these certificate transparency logs. So I read our own log, and here’s what anyone could learn about CertKit from them.

AI is making social engineering attacks significantly more effective, according to a new report from cyber insurance firm Resilience. These attacks were behind more than 85% of losses in the first half of 2026, compared to less than 20% during H1 2024. “Losses tied to phishing, social engineering, and transfer fraud have climbed from 17.7% of incurred losses in H1 2024 to 85.3% in H1 2026, the single largest increase in the report’s five half-year comparison,” Resilience says.

A study has found that AI chatbots can be more effective at social engineering than human scammers, WIRED reports. The researchers looked at a form of romance scam commonly known as “pig butchering,” in which scammers spend weeks or months building a relationship with the victim before tricking them into sending money for a phony investment scheme.

Enterprise security teams need to secure a risk surface that is constantly changing. However, the tools in their stack were built to check only a fraction of that risk. For confirmation, they rely on static snapshots and annual attestations. I now see this as the defining problem in GRC. When 451 Research (S&P Global) initiated coverage of TrustCloud in this space, they described a clear and growing divide.

Agent observability tools capture traces, metrics, logs, and evaluations across AI agent workflows. They help teams reconstruct execution paths, inspect tool calls and handoffs, diagnose failures, and monitor latency, cost, and output quality. This guide also covers complementary security platforms that discover agents, enforce runtime policies, or control the privileges agents receive. Agents don’t fail in straight lines.

A cyber loss model produces one distribution. How that distribution gets drawn changes what a reader can see in it, and the conventional projection hides the part most decisions depend on. ‍ The two views below contain identical data. One of them is close to unreadable for anything except the extreme tail, and the difference is worth understanding before the next time somebody asks what the number means. ‍

Human oversight is the only control in an AI program that can stop working while producing exactly the same evidence as when it worked. A failed encryption control throws errors. A monitoring pipeline that breaks stops delivering alerts. A review step that has become a formality still generates approvals, timestamps and sign-offs, and the compliance file looks identical. ‍ The asymmetry makes the design question secondary to the measurement one.