Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For decades, finding a zero-day flaw followed a predictable script: a highly skilled human researcher spent weeks staring at source code, digging for edge cases, and manually stitching together an exploit. In April 2026, Anthropic flipped that script by announcing Claude Mythos. This frontier model didn’t just mark an incremental upgrade; it introduced autonomous, machine-speed vulnerability hunting.

In May 2026, the Drupal Security Team disclosed a critical SQL injection vulnerability affecting Drupal core. The issue, tracked as CVE-2026-9082, affects Drupal installations using PostgreSQL and has been assigned a Drupal security risk rating of 23/25. The vulnerability can be exploited by anonymous users, and Drupal has confirmed that exploit attempts are being detected in the wild.

Most data security posture management (DSPM) programs don't fail because the technology is wrong. They fail because of execution gaps, from incomplete data inventory to misclassified data at scale to fragmented cloud environments and teams stretched too thin to act on findings. However, each of these problems is predictable, and each has a known fix.

Code from GitHub and Grafana is in criminal hands. Secrets buried inside could open doors no one is thinking of protecting yet, and AI will make hunting 0-days in that private code faster than ever.

Let’s start with a scenario. This is illustrative, not a single reported incident. A developer shares a Postman collection in Slack to move faster. “Here’s the Postman collection for the payment API. It has live auth headers so you can test prod endpoints.” The team uses it, work gets done, and the link stays. What no one realizes is that the collection lives inside a public Postman workspace. Weeks later, it is indexed by search engines. The URL requires no login.

Most organizations think MFA and rate limiting are enough to stop credential stuffing. They aren’t. Attackers have adapted, and the controls that worked five years ago are now routinely bypassed using residential proxy networks, low-and-slow automation, and real-time session token interception.

There is no question that AI is changing cybersecurity in a massive way. In many respects, its impact is comparable to the rise of the internet. AI tools are helping organizations improve efficiency, automate repetitive tasks, and process data at a speed humans simply cannot match. Unfortunately, the same technology helping defenders is also being adopted by cybercriminals just as quickly. For cybersecurity professionals, keeping up with AI and agentic developments is no longer optional.

2026 has officially become the year of speed, scale and support. The delta between a phishing email landing and a full organizational compromise has shrunk to mere seconds. The reality by the numbers: To close this window, your defense strategy must evolve into a two-step strategy of accuracy and automation.

In today’s cybersecurity landscape, speed is often treated as the ultimate objective. Organizations are racing to adopt AI-driven technologies, automate workflows, reduce response times, and deliver faster outcomes. Digital forensics is no exception. Forensic examiners increasingly rely on tools that automate large parts of the analysis process, helping reduce the time required for complex investigations. But this raises an important question: at what cost?

Microsoft Exchange and Outlook email services are among the most popular email applications in business environments. Sometimes, new users cannot find old emails in the Outlook client or Outlook web application after three or twelve months. One of the possible reasons may be improper synchronization settings in Outlook. Read this blog post to discover how you can find old emails and get Outlook emails back.