Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Sr. Technical Content Strategist From Advisory AI to Operational AI in Security Operations The early wave of AI SOC platforms has delivered mixed results. While AI proved its usefulness as a triage assistant and next-step remediation advisor, these benefits came with significant drawbacks. Foremost, the cost of outsourcing an AI SOC is significant. Medium enterprises could expect to pay anywhere from $120,000 – $360,000 a year for the service.

Today, let's take a closer look at incident response playbooks: how to build one, tailor it for secret leaks, take actions, and learn from incidents.

The security landscape has shifted dramatically. Employees now work across dozens of applications, browsers, and devices—often using personal accounts alongside corporate ones. They're adopting generative AI tools at unprecedented rates, and your source code is moving between repositories faster than traditional DLP tools can detect. This creates a fundamental problem: how do you enable productive work while preventing corporate IP from leaving your trusted environment?

In May 2025, Coinbase disclosed a data breach that exposed nearly 70,000 customer records—not through a sophisticated external attack, but through bribed customer service agents. The cryptocurrency exchange refused a $20 million ransom demand and instead pledged that amount toward catching those responsible. One arrest has been made in India, but the incident highlights a fundamental problem in modern security: your people can become your greatest vulnerability.

In large-scale security environments, the primary challenge is often execution rather than a lack of detection. When multiple security tools report the same missing patch on a single machine, it creates hundreds of redundant findings that inflate backlogs and cause ticket-based workflows to break down. By aggregating these overlapping alerts into a single remediation action centered on the root cause, organizations can align their work with actual outcomes.

Doing business in Ireland in 2026 means operating in one of Europe’s most active cloud and data ecosystems and one of its most targeted cyber threat environments. As a leading hub for global technology, financial services, and data-driven enterprises, organizations across Ireland face growing pressure to strengthen their cybersecurity posture.

If you haven’t heard yet, Netwrix recently formed a dedicated in-house Security Research team on July 15, 2025. The team focuses on producing research across areas like identity, data security, AI, and cloud, while also translating publicly available research into practical improvements across our product portfolio so customers can benefit from it.

AI agents are about to cross a threshold. For infrastructure and security leaders, agentic AI is no longer an innovation topic but a production readiness problem. What started as sandboxed applications and tech demos at trade shows (bet you’ve seen a few of those) has morphed into long-running autonomous actors operating directly in production cloud and on-prem infrastructure. They read data, write code, deploy services, access databases, and make decisions continuously across environments.

When vulnerability remediation succeeds at enterprise scale, it’s very rarely because the vulnerability management team is finding more vulnerabilities. It’s because the program was built around the idea of turning messy findings into steady, measurable risk reduction. That’s not an easy task. It’s easier to make it a numbers game, pointing to vulnerability volumes and how many findings were addressed, rather than accurately depicting how much real risk was eliminated.