MDR | Breaking Cybersecurity News | The Hacker News

Building a shortlist for an AI SOC evaluation can be tough. SIEM, SOAR, and pureplay AI SOC vendors are all saying the same thing. But behind the identical label sit very different products, from chat assistants bolted onto a legacy SIEM to agent platforms that run detection, triage, investigation, and response on their own data foundation. Whether a platform will materially change outcomes for your team matters more than what it is called. We can measure that in investigation time, false-positive volume, analyst hours returned, total cost of running your SOC and finally whether the architecture will hold up 2-3 years from now as the volume, speed and complexity of attacks keep increasing. What Is an AI SOC Platform? An AI SOC platform is a security operations platform where AI agents carry out the core work of the SOC (detection, triage, investigation, and response) by reasoning over correlated security data, under human oversight. It differs from bolt-on AI, which summarizes ...

For most of the past decade, managed detection and response was the answer to a real problem. Security teams couldn't staff around the clock, couldn't hire enough analysts, and needed someone else to handle the alert queue. MDR stepped in. It worked well enough. Until now. The threat landscape has changed faster than the MDR model can adapt. Attackers are using AI to move faster, generate more convincing phishing at scale, automate reconnaissance, and create malware variants that evade signature-based detection. The attack surface has expanded from endpoint to cloud, identity, and network simultaneously. And yet MDR is still doing what it always did. Routing alerts to human analysts who triage what they can, in the order they can get to it. That is no longer enough. The data we share below proves it and security leaders might consider exploring whether they have outgrown their MDR . MDR's 24/7 promise doesn't cover 60% of your alerts MDR promised 24/7 human cov...

Why do the Riskiest SOC Alerts Go Unanswered? Security operations teams are drowning in alerts. But the real problem isn't always alert volume; it's the blind spots. The most dangerous alerts are the ones no one is investigating. A recent report from The Hacker News examined why certain high-risk alert categories - WAF, DLP, OT/IoT, dark web intelligence, and supply chain signals- consistently go uninvestigated across enterprise SOCs. The findings point to a structural gap in how security coverage is delivered today: not a lack of tooling, but a ceiling built into every existing model. Your SOC Model Has a Coverage Ceiling In-house SOC teams are the first to feel the gap. Overloaded with high-volume, routine alerts, analysts rarely have the capacity, or the specialized expertise, to investigate WAF events, DLP anomalies, or signals from operational technology environments. These alert types require deep, domain-specific knowledge that most SOC teams simply don't have...

For mid-market organizations, cybersecurity is a constant balancing act. Proactive, preventative security measures are essential to protect an expanding attack surface. Combined with effective protection that blocks threats, they play a critical role in stopping cyberattacks before damage is done. The challenge is that many security tools add complexity and cost that most mid-market businesses can’t absorb. With limited budgets and lean IT and security teams, organizations often focus on detection and response. While necessary, this places a significant operational burden on teams already stretched thin. A more sustainable approach is security across the complete threat lifecycle—combining prevention, protection, detection, and response in a way that reduces risk without increasing cost or complexity. Why Mid-Market Security Often Feels Stuck Most mid-market organizations rely on a small set of foundational tools, such as endpoint protection, email security, and network firewalls....