U.S. Department of Justice unsealed a federal indictment in Los Angeles against 16 defendants of DanaBot, a Russia-based malware-as-a-service (MaaS) operation responsible for orchestrating massive fraud schemes, enabling ransomware attacks and inflicting tens of millions of dollars in financial losses to victims. Agentic AI played a central role in dismantling DanaBot, orchestrating predictive threat modeling, real-time telemetry correlation, infrastructure analysis and autonomous anomaly detection. These capabilities reflect years of sustained R&D and engineering investment by leading cybersecurity providers, who have steadily evolved from static rule-based approaches to fully autonomous defense systems. Taking down DanaBot validated agentic AI’s value for Security Operations Centers (SOC) teams by reducing months of manual forensic analysis into a few weeks. All that extra time gave law enforcement the time they needed to identify and dismantle DanaBot’s sprawling digital footprint quickly. DanaBot’s takedown signals a significant shift in the use of agentic AI in SOCs. SOC Analysts are finally getting the tools they need to detect, analyze, and respond to threats autonomously and at scale, attaining the greater balance of power in the war against adversarial AI. Agentic AI directly addresses a long-standing challenge, starting with alert fatigue. Microsoft research reinforces this advantage, integrating gen AI into SOC workflows and reducing incident resolution time by nearly one-third. DanaBot’s dismantling signals a broader shift underway: SOCs are moving from reactive alert-chasing to intelligence-driven execution. At the center of that shift is agentic AI. SOC leaders getting this right aren’t buying into the hype. They’re taking deliberate, architecture-first approaches that are anchored in metrics and, in many cases, risk and business outcomes.