Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

On May 5, 2026, at roughly 19:30 UTC, DENIC, the registry operator for the.de country-code top-level domain (TLD), started publishing incorrect DNSSEC signatures for the.de zone. Any validating DNS resolver receiving these signatures was required by the DNSSEC specification to reject them and return SERVFAIL to clients, including 1.1.1.1, the public DNS resolver operated by Cloudflare. The country-code top-level domain for Germany, .de, is one of the largest on the Internet.

Anyone who's stood up a SIEM from scratch knows the feeling: weeks of infrastructure work, integration headaches, and a services team alongside for the whole process. That experience shaped how people think about adopting anything new in security ops. The instinct is to treat AI the same way: budget for it, plan for it, bring in specialists. This instinct is costing teams real time. Traditional infrastructure takes great effort to stand up. Infrastructure-as-code happens in seconds.

Researchers at Google’s Threat Intelligence Group (GTIG) are tracking a new threat actor that’s impersonating help desks to trick users into installing malware. The threat actor, which GTIG tracks as “UNC6692,” begins by sending a large volume of spam emails to the victim, then initiates contact via Microsoft Teams to ostensibly help the user block the spam.

There is a lot of panic around Claude Mythos. Some people are saying it will hack every system, that the sky is falling, and that there is no stopping it. That fear is dangerous because it makes teams freeze. Claude Mythos is genuinely powerful. AI systems like this can find security issues in minutes that even experienced penetration testers might take weeks to identify and exploit. That part is real. But here is the important point: AI is still exploiting what is already there.

If you ask any MSP what they use to protect their clients’ cloud environments, you will get one of two answers. Either they’ll point to the native security tools built into platforms like Microsoft 365 or Google Workspace. Or they’ll describe a patchwork of different products stitched together to cover identity, configuration, and SaaS visibility. Neither approach is ideal. But both reflect the reality MSPs are working with today.

MSPs are managing more customers, more environments, and more tools than ever before. At the same time, customer expectations keep rising -- faster response times, clearer reporting, and consistent service across every client. All of that pressure lands on already‑lean teams. That’s the reality Rai was built for.

Security is tied to business operations in many (often unappreciated) ways, but the connection is rarely more visible or consequential than during an acquisition or partnership. In those deals, a company stakes its reputation and finances on another company, and a lapse in security can throw the whole thing into chaos.

In May 2025, a developer using Claude with the GitHub MCP server asked their AI assistant to do something entirely routine: review the open issues in a public repository. The repository contained a malicious GitHub issue planted by a researcher demonstrating a security vulnerability. The issue contained hidden instructions. The AI read them, followed them, accessed the developer's private repositories, and posted the contents in a publicly visible pull request. No credentials were stolen.

Most enterprise fraud stacks are built to detect account takeover after it’s already succeeded. Login anomaly rules fire at authentication. Transaction models fire at monetization. By both points, the attacker is already inside. Knowing how to detect account takeover in real-time means shifting detection upstream – to behavioral signals, device trust, credential exposure feeds, and session integrity monitoring that activate before any fraudulent transaction is attempted.

Managing a growing list of vendors can add complexity across an organization. Adding a new partner may require navigating additional administrative processes and internal alignment. As a result, third-party DevOps backup often ends up lower on the priority list until one serious data deletion, prolonged recovery, or failed restore turns it from a “nice to have” into an executive-level decision.